DMBOK2.0全知识点总结（第1-3章 数字管理 数字伦理 数字治理）

CDMP，全称Certified for Data Management Professional，即数据管理专业人士认证，由数据管理国际协会DAMA International建立，是一项涵盖学历教育、工作经验和专业知识考试在内的综合认证。 总结了CDMP英文考试的所有知识点，考点，以及历史真题。 适用于从事数据管理，数据治理，数字转型等方面的高级职业认证。 章节和知识点较多，因此分章节和完成时间分发。

DAMA章节1-3知识点+真题

• Chapter 1: Data Management 数据管理
  • 1. Introduction 引言
    • 1.1. Definition
      • 1.1.1. Data Management is the development, execution, and supervision of plans, policies, programs, and practices that deliver, control, protect, and enhance the value of data and information assets throughout their lifecycles.
        • 21. Data management is the development，execution and supervision of plans policies，Programs and practices that deliver control protect and enhance: A：enterprise management capabilities B：the value of information assets C：the value of data and information assets. D：data and information assets E：the value of data assets 正确答案：C 你的答案：D 解析：1.1：数据管理（Data Management）是为了交付、控制、保护并提升数据和信息资产的价值，在其整个生命周期中制订计划、制度、规程和实践活动，并执行和监督的过程。
      • 1.1.2. A Data Management Professional is any person who works in any facet of data management to meet strategic organizational goals. Data management professionals fill numerous roles, from the highly technical (e.g., database administrators, network administrators, programmers) to strategic business (e.g., Data Stewards, Data Strategists, Chief Data Officers).
        • 13. Speed of implementation is one of the benefits of the__ model for data stewardship implementation A：Data Steward by Function B：Data Steward by Business Process C：Data Steward by project 按项目划分的数据管家 D：Data Steward by Subject Area E：all 正确答案：C 你的答案：E 解析：项目project 对应被实现 implementation，比如各种agile项目流程。
    • 1.2. Business driven
      • 1.2.1. The primary driver for data management is to enable organizations to get value from their data assets, just as effective management of financial and physical assets enables organizations to get value from those assets.
    • 1.3. Goals
      • 1.3.1. Understanding and supporting the information needs of the enterprise and its stakeholders, including customers, employees, and business partners
      • 1.3.2. Capturing, storing, protecting, and ensuring the integrity of data assets
        • 8. The fact that information systems often do NOT address the critical problems of a business as a whole is most likely an indication of the need for improved （对症需求） A：information systems planning B：service oriented methodologies C：database management systems D：information systems architecture E：Enterprise Service Bus 企业服务总线 正确答案：A 你的答案：D 解析：除A外，其他比较具体，不够宏观发现关键问题相关章节内容：1.1数据管理（Data Management）是为了交付、控制、保护并提升数据和信息资产的价值，在其整个生命周期中制订计划、制度、规程和实践活动，并执行和监督的过程。
      • 1.3.3. Ensuring the quality of data and information
      • 1.3.4. Ensuring the privacy and confidentiality of stakeholder data
      • 1.3.5. Preventing unauthorized or inappropriate access, manipulation, or use of data and information
        • 2. Data Management goals include each of the following EXCEPT A：long-term benefit. B：success measured by effectiveness of enterprise data use C：success measured by the effectiveness of a single application D：application independence E：all 正确答案：C 你的答案：D 解析：正确答案：C来源：1.1.2题解： a single application 错误1.1.2 目标组织管理数据的目标包括：1）理解并支撑企业及其利益相关方（包括客户、员工和业务合作伙伴等）的信息需求得到满足。2）获取、存储、保护数据和确保数据资产的完整性。3）确保数据和信息的质量。4）确保利益相关方的数据隐私和保密性。5）防止数据和信息未经授权或被不当访问、操作及使用。（提示应用独立D）6）确保数据能有效地服务于企业增值的目标。
      • 1.3.6. Ensuring data can be used effectively to add value to the enterprise
      • 1.3.7. 18. which of the following is not a goal of data management? A：Preventing unauthorized access ， manipulation or use of data and information B：Capturing, storing,protecting and ensuring the integrity of data assets C：Understanding the process needs of the enterprise D：Ensuring the quality of data and information E：Ensuring the privacy and confidentiality of stakeholder data 正确答案：C 你的答案：C 解析：了解企业过程并不是数据管理的目的
  • 2. Essential Concepts 基本概念
    • 2.1. Data
      • 2.1.1. Long-standing definitions of data emphasize its role in representing facts about the world
      • 2.1.2. In relation to information technology, data is also understood as information that has been stored in digital form
      • 2.1.3. Data is both an interpretation of the objects it represents and an object that must be interpreted (Sebastian-Coleman, 2013).
    • 2.2. Data and Information
      • 2.2.1. Data has been called the “raw material of information” and information has been called “data in context”
      • 2.2.2. Often a layered pyramid is used to describe the relationship between data (at the base), information, knowledge, and wisdom (at the very top).
        • It is based on the assumption that data simply exists. But data does not simply exist. Data has to be created.
        • By describing a linear sequence from data through wisdom, it fails to recognize that it takes knowledge to create data in the first place.
        • It implies that data and information are separate things, when in reality, the two concepts are intertwined with and dependent on each other. Data is a form of information and information is a form of data.
        • DIKW 信息收敛模型
          • Data
          • Information
          • Knowledge
          • Wisdom
      • 2.2.3. 5. The importance of information is expressed in what types of values? A：Missing and complete 缺失与完整 B：Inconsistent and consistent 不持续和持续 C：Realized and potential 已实现和潜力的 D：Non-atomic and atomic 非原子性和原子性 E：All 正确答案：C 你的答案：C 解析：排除法，A和B是数据属性，D是操作属性，C是价值属性
    • 2.3. Data as an Organizational Asset
      • 2.3.1. An asset is an economic resource, that can be owned or controlled, and that holds or produces value.
      • 2.3.2. value of goodwill 商誉价值
      • 2.3.3. In the early 1990s, some organizations found it questionable whether the value of goodwill should be given a monetary value. Now, the ‘value of goodwill’ commonly shows up as an item on the Profit and Loss Statement (P&L). Similarly, while not universally adopted, monetization of data is becoming increasingly common. It will not be too long before we see this as a feature of P&Ls.
    • 2.4. Data Management Principles
      • 2.4.1. Effective data management requires leadership commitment
        • Data management involves a complexset of processes that, to be effective, require coordination, collaboration, and commitment. Getting thererequires not only management skills, but also the vision and purpose that come from committedleadership.
      • 2.4.2. Data is an asset with unique properties
        • Data is an asset, but it differs from other assets in importantways that influence how it is managed. The most obvious of these properties is that data is not consumed when it is used, as are financial and physical assets.
      • 2.4.3. The value of data can and should be expressed in economic terms
        • Calling data an asset implies that it has value. While there are techniques for measuring data’s qualitative and quantitative value, there are not yet standards for doing so.
      • Data is valuable
      • 2.4.4. Managing data means managing the quality of data
        • Ensuring that data is fit for purpose is a primarygoal of data management. To manage quality, organizations must ensure they understand stakeholders’requirements for quality and measure data against these requirements.
      • 2.4.5. It takes Metadata to manage data
        • The data used to manage and use data is called Metadata. Metadata originates from a range of processes related to data creation,processing, and use, including architecture, modeling, stewardship, governance, Data Qualitymanagement, systems development, IT and business operations, and analytics
      • 2.4.6. It takes planning to manage data
        • Data is created in many places and is moved between places for use. To coordinatework and keep the end results aligned requires planning from an architectural and process perspective.
      • 2.4.7. Data management requirements must drive Information Technology decisions
        • Data and datamanagement are deeply intertwined with information technology and information technologymanagement. Managing data requires an approach that ensures technology serves, rather than drives, anorganization’s strategic data needs.
      • Data Management Requirements are Business Requirements
      • 2.4.8. Data management is cross-functional; it requires a range of skills and expertise
        • A single team cannotmanage all of an organization’s data. Data management requires both technical and non-technical skillsand the ability to collaborate.
      • 2.4.9. Data management requires an enterprise perspective
        • Data management has local applications, but itmust be applied across the enterprise to be as effective as possible. This is one reason why datamanagement and data governance are intertwined.
      • 2.4.10. Data management must account for a range of perspectives
        • Data is fluid. Data management must constantly evolve to keep up with the ways data is created and used and the data consumers who use it.
          • 25. All of the following is true for information metrics EXCEPT A：metrics are used to measure the success of a data governance program B：an organization should have relatively few KPls. C：metrics should all be on the same level (no hierarchy) D：metrics should be real，objective measures E：all 正确答案：C 你的答案：C 解析：指标可以有宏观的也可以有子级给不同人和不同人使用
      • Data Management depends on diverse skills
      • 2.4.11. Different types of data have different lifecycle characteristics
        • Data has a lifecycle and managing data requires managingits lifecycle. Because data begets more data, the data lifecycle itself can be very complex. Datamanagement practices need to account for the data lifecycle.
      • 2.4.12. Managing data includes managing the risks associated with data
        • In addition to being an asset, dataalso represents risk to an organization. Data can be lost, stolen, or misused. Organizations must considerthe ethical implications of their uses of data. Data-related risks must be managed as part of the datalifecycle.
      • Data Management is lifecycle management
      • 2.4.13. 3. Data Management principles include each of the following EXCEPT A：the realization that NOT every technology investment will make money B：a commitment to the integration of business and technology goal and strategies C：the concept that end users are the owners of the data D：that time must be set aside for Information Systems services E：All 正确答案：A 你的答案：C 解析：A无关，太宽泛了，跟原则无关。1.2.4
    • 2.5. Data Management Challenges
      • 2.5.1. Data Differs from Other Assets
        • Data is not tangible. Yet it is durable; it does not wear out 消耗, though the value of data often changes as it ages.
        • Data is easy to copy and transport. But it is not easy to reproduce if it is lost or destroyed. Because it is not consumed when used, it can even be stolen without being gone.
        • Data is dynamic and can be used for multiple purposes. The same data can even be used by multiple people at the same time
        • Many uses of data beget more data. Most organizations must manage increasing volumes of data and the relation between data sets.
        • 14. The flow of data in an Information Supply Chain (lS is comparable to a manufacturer' s Supply Chain in all of the following ways EXCEPT raw data A：is assembled 组装 into useful information B：comes from its sources C：is refined 打磨 through transformation processes D：can be substituted 取代 from competitive sources 竞争来源 E：none 正确答案：D 你的答案：D 解析：原始数据是无法被竞争来源替代的
      • 2.5.2. Data Valuation
        • 1. Cost of obtaining and storing data
        • 2. Cost of replacing data if it were lost
        • 3. Impact to the organization if data were missing
        • 4. Cost of risk mitigation and potential cost of risks associated with data
        • 5. Cost of improving data
        • 6. Benefits of higher quality data
        • 7. What competitors would pay for data
        • 8. What the data could be sold for
        • 9. Expected revenue from innovative uses of data
      • 2.5.3. Data Quality
        • managing Data Quality is not a one-time job
        • Costs come from
          • 1. Scrap and rework
          • 2. Work-arounds and hidden correction processes
          • 3. Organizational inefficiencies or low productivity
          • 4. Organizational conflict
          • 5. Low job satisfaction
          • 6. Customer dissatisfaction
          • 7. Opportunity costs, including inability to innovate
          • 8. Compliance costs or fines 罚款
          • 9. Reputational costs
        • Benefits of high quality data include
          • 1. Improved customer experience
          • 2. Higher productivity
          • 3. Reduced risk
          • 4. Ability to act on opportunities
          • 5. Increased revenue
          • 6. Competitive advantage gained from insights on customers, products, processes, and opportunities
      • 2.5.4. Planning for Better Data
        • 1. It starts with the recognition that organizations can control how they obtain and create data. If they view data as a product that they create, they will make better decisions about it throughout its lifecycle.
          • involve
            • The ways data connects business processes that might otherwise be seen as separate
            • The relationship between business processes and the technology that supports them
            • The design and architecture of systems and the data they produce and store
            • The ways data might be used to advance organizational strategy
        • 2. Planning for better data requires a strategic approach to architecture, modeling, and other design functions. It also depends on strategic collaboration between business and IT leadership. And, of course, it depends on the ability to execute effectively on individual projects.
        • 3. The challenge is that there are usually organizational pressures, as well as the perennial pressures of time and money, that get in the way of better planning. Organizations must balance long- and short-term goals as they execute their strategies. Having clarity about the trade-offs leads to better decisions.
      • 2.5.5. Metadata and Data Management
        • Organizations require reliable Metadata to manage data as an asset. Metadata in this sense should be understood comprehensively. It includes not only the business, technical, and operational Metadata described in Chapter 12, but also the Metadata embedded in Data Architecture, data models, data security requirements, data integration standards, and data operational processes.
        • Metadata describes what data an organization has, what it represents, how it is classified, where it came from, how it moves within the organization, how it evolves through use, who can and cannot use it, and whether it is of high quality. Data is abstract. 数据是抽象的 Definitions and other descriptions of context enable it to be understood. They make data, the data lifecycle, and the complex systems that contain data comprehensible.
          • 10. Meta-data in an organization is used to A：specify subject and usage and provide for an indirect maimer 残害者 to reach it using object-oriented methods 面向对象的方法 B：manage its information resources effectively and efficiently C：details time, scope sensitivity of the data D：manage its data resource personnel effectively. E：all 正确答案：B 你的答案：E 解析：1.2.5：元数据描述了一个组织拥有什么数据，它代表什么、如何被分类、它来自哪里、在组织之内如何移动、如何在使用中演进、谁可以使用它以及是否为高质量数据。数据是抽象的，上下文语境的定义和其他描述让数据清晰明确。它们使数据、数据生命周期和包含数据的复杂系统易于理解。
        • The challenge is that Metadata is a form of data and needs to be managed as such. Organizations that do not manage their data well generally do not manage their Metadata at all. Metadata management often provides a starting point for improvements in data management overall.
      • 2.5.6. Data Management is Cross-functional
        • 1. Data management is a complex process. Data is managed in different places within an organization by teams that have responsibility for different phases of the data lifecycle. Data management requires design skills to plan for systems, highly technical skills to administer hardware and build software, data analysis skills to understand issues and problems, analytic skills to interpret data, language skills to bring consensus to definitions and models, as well as strategic thinking to see opportunities to serve customers and meet goals.
        • 2. The challenge is getting people with this range of skills and perspectives to recognize how the pieces fit together so that they collaborate well as they work toward common goals.
      • 2.5.7. Establishing an Enterprise Perspective
        • Managing data requires understanding the scope and range of data within an organization. Data is one of the ‘horizontals 横向领域’ of an organization. It moves across verticals, such as sales, marketing, and operations… Or at least it should. Data is not only unique to an organization; sometimes it is unique to a department or other sub-part of an organization. Because data is often viewed simply as a by-product of operational processes (for example, sales transaction records are the by-product of the selling process), it is not always planned for beyond the immediate need.
        • Even within an organization, data can be disparate. Data originates in multiple places within an organization. Different departments may have different ways of representing the same concept (e.g., customer, product, vendor). As anyone involved in a data integration or Master Data Management project can testify, subtle (or blatant) differences in representational choices present challenges in managing data across an organization. At the same time, stakeholders assume that an organization’s data should be coherent, and a goal of managing data is to make it fit together in common sense ways so that it is usable by a wide range of data consumers.
        • One reason data governance has become increasingly important is to help organizations make decisions about data across verticals 跨垂直领域.
      • 2.5.8. Accounting for Other Perspectives
        • Today’s organizations use data that they create internally, as well as data that they acquire from external sources. They have to account for different legal and compliance requirements across national and industry lines. People who create data often forget that someone else will use that data later. Knowledge of the potential uses of data enables better planning for the data lifecycle and, with that, for better quality data. Data can also be misused. Accounting for this risk reduces the likelihood of misuse.
      • 2.5.9. The Data Lifecycle
        • Understanding the data lineage requires documenting the origin of data sets, as well as their movement and transformation through systems where they are accessed and used.
        • The focus of data management on the data lifecycle has several important implications:
          • 1. Creation and usage are the most critical points in the data lifecycle
          • 2. Data Quality must be managed throughout the data lifecycle
          • 3. Metadata Quality must be managed through the data lifecycle
          • 4. Data Security must be managed throughout the data lifecycle
          • 5. Data Management efforts should focus on the most critical data
            • ROT
              • (Data that is Redundant 冗余的, Obsolete 过时的, Trivial 碎片化的)
      • 2.5.10. Different Types of Data
        • By Type 1
          • Transactional data
          • Reference Data
          • Master Data
          • Metadata
        • By Type 2
          • Category data
          • Resource data
          • Event data
          • Detailed transaction data
        • By Content
          • Data domains
          • Subject areas
        • By Format
        • By the level of protection
        • By how and where it is stored or accessed
      • 2.5.11. Data and Risk
        • Data not only represents value, it also represents risk. Low quality data (inaccurate, incomplete, or out-of-date) obviously represents risk because its information is not right. But data is also risky because it can be misunderstood and misused.
        • The increased role of information as an organizational asset across all sectors has led to an increased focus by regulators and legislators on the potential uses and abuses of information. it is clear that, while we are still waiting for Accounting to put Information on the balance sheet as an asset, the regulatory environment increasingly expects to see it on the risk register, with appropriate mitigations and controls being applied.
          • Sarbanes-Oxley
            • focusing on controls over accuracy and validity of financial transaction data from transaction to balance sheet
          • Solvency II
            • focusing on data lineage and quality of data underpinning risk models and capital adequacy in the insurance sector
          • data privacy regulations
            • covering the processing of data about people across a wide range of industries and jurisdictions
        • Likewise, as consumers become more aware of how their data is used, they expect not only smoother and more efficient operation of processes, but also protection of their information and respect for their privacy
      • 2.5.12. Data Management and Technology
        • the concept of data management has been deeply intertwined with management of technology. That legacy continues. In many organizations, there is ongoing tension between the drive to build new technology and the desire to have more reliable data – as if the two were opposed to each other instead of necessary to each other.
        • Successful data management requires sound decisions about technology, but managing technology is not the same as managing data. Organizations need to understand the impact of technology on data, in order to prevent technological temptation from driving their decisions about data. Instead, data requirements aligned with business strategy should drive decisions about technology.
          • 7. Joint Application Design 联合应用设计 JA techniques are LEAST appropriate 最不合适的for A：developing a strategy for upward-compatibility 向上兼容when planning for a DBMS upgrade B：working with programmers for system development. C：obtaining user requirements D：developing a project plan E：none 正确答案：A 你的答案：C 解析：Joint application design（JAD）is a process used in the life cycle area of the dynamic systems development method（DSDM）to collect business requirements while developing new information systems for a company.
      • 2.5.13. Effective Data Management Requires Leadership and Commitment
        • The Leader's Data Manifesto (2017)
        • Although most organizations recognize their data as an asset, they are far from being data-driven. Many don’t know what data they have or what data is most critical to their business. They confuse data and information technology and mismanage both. They do not approach data strategically. And they underestimate the work involved with data management. These conditions add to the challenges of managing data and point to a factor critical to an organization’s potential for success: committed leadership and the involvement of everyone at all levels of the organization.
          • 6. Marketing the value of Data Management services should be done to A：the entire organization B：information technology. C：ls project managers D：business groups E：all 正确答案：A 你的答案：A 解析：1.2.3题解：A最合理，如今的组织依靠数据资产做出更高效的决定，并拥有更高效的运营。企业运用数据去理解他们的客户，创造出新的产品和服务，并通过削减成本和控制风险的手段来提高运营效率。政府代理机构、教育机构以及非营利组织也需要高质量的数据来指导他们的运营、战术和战略活动。随着大量组织越来越依赖数据，可以更清楚地确定数据资产的价值。许多组织把自己定义为“数据驱动“型组织。想要保持竞争力的企业必须停止基于直觉或感觉做出决策，而是使用事件触发和应用分析来获得可操作的洞察力。数据驱动包括认识到必须通过业务领导和技术专业知识的合作关系，以专业的规则高效地管理数据。
        • Advocacy for the role of Chief Data Officer (CDO) stems from a recognition that managing data presents unique challenges and that successful data management must be business-driven, rather than IT-driven. A CDO can lead data management initiatives and enable an organization to leverage its data assets and gain competitive advantage from them. However, a CDO not only leads initiatives. He or she must also lead cultural change that enables an organization to have a more strategic approach to its data.
          • 11. The information strategy should primarily be aligned with A：performance and sustainability objectives of tile 平铺的 organization B：vision and mission of the data governance organization C：vision of the clo. D：technology strategy. E：none 正确答案：A 你的答案：B 解析：与组织目标和战略对齐
          • 27. Factors relevant 相关因素 to data management initiatives include each of the following EXCEPT A：IT project portfolio participation B：organizational and cultural change C：that data management initiatives often required cross functional sponsorship from the Data governance Council D：that every data management project should follow the project management standards of the organization E：all 正确答案：A 你的答案：D 解析：A是IT相关，非数据管理相关
    • 2.6. Data Management Strategy
      • 2.6.1. A data strategy should include business plans to use information to competitive advantage and support enterprise goals. Data strategy must come from an understanding of the data needs inherent in the business strategy: what data the organization needs, how it will get the data, how it will manage it and ensure its reliability over time, and how it will utilize it.
        • The following points are true about the relationship between the strategic business plan and the enterprise data strategy EXCEPT A：business management should participate in the creation of both the enterprise data strategy and the strategic business plan B：the enterprise data strategy is driven by the strategic business plan C：the enterprise data strategy should be started first D：the enterprise data planning process often causes reexamination of the strategic business plan E：All 正确答案：C 你的答案：C 解析：正确答案：C来源：1.3.4题解：业务更早，书中贯穿数据服务于业务的思想。 彼得·艾肯（Peter Aiken）的框架中使用DMBOK知识领域来描述许多组织演化的情况。使用此框架，组织可定义一种演化路径，达到拥有可靠的数据和流程的状态，支持战略业务目标的实现
      • 2.6.2. Typically, a data strategy requires a supporting Data Management program strategy – a plan for maintaining and improving the quality of data, data integrity, access, and security while mitigating known and implied risks. The strategy must also address known challenges related to data management.
      • 2.6.3. The data management strategy should address all DAMA Data Management Framework Knowledge Areas relevant to the organization.
      • 2.6.4. The components of a data management strategy should include:
        • 1. A compelling vision for data management
        • 2. A summary business case for data management, with selected examples
        • 3. Guiding principles, values, and management perspectives
        • 4. The mission and long-term directional goals of data management
        • 5. Proposed measures of data management success
        • 6. Short-term (12-24 months) Data Management program objectives that are SMART (specific, measurable, actionable, realistic, time-bound)
        • 7. Descriptions of data management roles and organizations, along with a summary of their responsibilities and decision rights
        • 8. Descriptions of Data Management program components and initiatives
        • 9. A prioritized program of work with scope boundaries 概要计划
        • 10. A draft implementation roadmap with projects and action items
      • 2.6.5. Deliverables from strategic planning for data management include:
        • 1. A Data Management Charter 管理章程
          • Overall vision, business case, goals, guiding principles, measures of success, critical success factors, recognized risks, operating model, etc.
        • 2. A Data Management Scope Statement 范围声明
          • Goals and objectives for some planning horizon (usually 3 years)and the roles, organizations, and individual leaders accountable for achieving these objectives.
            • 16. A document that describes how data will be made more accessible over 3-5 years is called A：an analytics strategy B：data quality metrics C：a data collection standard D：a data management strategy E：a data warehouse design 正确答案：D 你的答案：D 解析：其他和当前选项相比不恰当，数据管理包含访问权限和retention保存策略
        • 3. A Data Management Implementation Roadmap 实施路线图
          • Identifying specific programs, projects, taskassignments, and delivery milestones
  • 3. Data Management Frameworks 数据管理框架
    • 3.1. Strategic Alignment Model 战略一致性模型
      • 
      • 3.1.1. Data align with business
      • 3.1.2. IT align with business
    • 3.2. The Amsterdam Information Model 阿姆斯特丹信息模型1
      • 
      • 3.2.1. 17. lnformation governance and data governance should be A：managed by the chief lnformation Officer B：managed as a single function C：managed as integrated functions ， with information governance reporting to data governance D：managed as integrated functions with data governance reporting to information governance E：managed as separate functions. 正确答案：E 你的答案：C 解析：1.3.2网姆断特丹信息横型网姆斯特丹信息模型（The Amsterdam Information Model，AlM）与战略一致性模型一样，从战略角度看待业务和IT的一致性（Abcoower、Maes和Truijens，1997），共有9个单元，它抽象出一个关注结构（包括规划和架构）和策略的中间层。DAMA-DMBOK框架更加深入地介绍了构成数据管理总体范围的知识领域，通过3幅圈描述了DAMA的数据管理框架：1）DAMA车轮圈（圈1-5）。
    • high-levelrelationships that influence how an organization manages data.
    • 3.3. The DAMA-DMBOK Framework
      • 3.3.1. The DAMA Wheel 车轮图
        • 
        • The DAMA Wheel defines the Data Management Knowledge Areas. It places data governance at the center of data management activities, since governance is required for consistency within and balance between the functions.
          • 23. The DAMA wheel contains A：maturity model dimensions B：knowledge areas C：data management deliverables D：data strategy initiatives E：data management processes 正确答案：B 你的答案：B 解析：1.3.3：DAMA车轮图定义了数据管理知识领域。它将数据治理放在数据管理活动的中心，因为治理是实现功能内部一致性和功能之间平衡所必需的。
        • The other Knowledge Areas (Data Architecture, Data Modeling, etc.) are balanced around the Wheel. They are all necessary parts of a mature data management function, but they may be implemented at different times, depending on the requirements of the organization.
        • 11个知识领域
      • 3.3.2. The Environmental Factors hexagon 环境因素六边形图
        • 
        • The Environmental Factors hexagon shows the relationship between people, process, and technology and provides a key for reading the DMBOK context diagrams. It puts goals and principles at the center, since these provide guidance for how people should execute activities and effectively use the tools required for successful data management.
          • 19. The DMBOK Environmental Factors hexagon' shows the relationship between A：inputs，activities and deliverables B：people，software and tools. C：business，application and technology architecture D：people，process and technology. E：DMBOK knowledge areas 正确答案：D 你的答案：D 解析：暂无解析
        • 知识领域结构的组成部分
      • 3.3.3. The Knowledge Area Context Diagram 知识领域语境关系图
        • 
        • describe the detail of the Knowledge Areas, including detail related to people, processes and technology. They are based on the concept of a SIPOC diagram used for product management (Suppliers, Inputs, Processes, Outputs, and Consumers). Context Diagrams put activities at the center, since they produce the deliverables that meet the requirements of stakeholders.
        • Each context diagram begins with the Knowledge Area’s definition and goals. Activities that drive the goals (center) are classified into four phases: Plan (P), Develop (D), Operate (O), and Control (C). On the left side (flowing into the activities) are the Inputs and Suppliers. On the right side (flowing out of the activities) are Deliverables and Consumers. Participants are listed below the Activities. On the bottom are Tools, Techniques, and Metrics that influence aspects of the Knowledge Area.
          • 1. Definition of the Knowledge Area.
          • 2. Goals
          • 3. Activities
            • a. (P) Planning Activities
            • b. (D) Development Activities
              • system development lifecycle (SDLC) (analysis, design, build, test, preparation, and deployment).
            • c. (C) Control Activities
            • d. (O) Operational Activities
          • 4. Inputs
          • 5. Deliverables
          • 6. Roles and Responsibilities
            • Skills Framework for the Information Age (SFIA)
          • 7. Suppliers
          • 8. Consumers
          • 9. Participants
          • 10. Tools
          • 11. Techniques
          • 12. Metrics
          • 22. Knowledge area activities are classified into four categories. They are A：Planning，Development，Control and Operations. B：Preparation，Detailing，Creating and Deployment. C：Procurement，Detailing, Control and Organizing D：Procurement，Development，Control and Operations E：Planning Detailing, control and Organizing 正确答案：A 你的答案：A 解析：1.3.3 3）活动。它是实现知识领域目标所需的行动和任务。一些活动按子活动、任务和步骤进行描述。活动分为4类，即计划、控制、开发和运营。
        • 每个知识领域概述
      • describes DataManagement Knowledge Areas, as defined by DAMA, and explains how their visual representation withinthe DMBOK.
      • 3.3.4. 24. The 'Data Management body of Knowledge is produced by: A：The Project Management Institute B：The Data Management Authority C：The Data Analysis Association D：The Data Management Association E：The data practitioner Association 正确答案：D 你的答案：D 解析：正确答案：D来源：1.1题解：随着专业领域的发展和成熟，为支持数据管理专业人员开展工作，DAMA国际数据管理协会出版了本书，即《DAMA数据管理知识体系指南》（第2版）。
    • 3.4. DMBOK Pyramid (Aiken) 金字塔
      • 
      • 3.4.1. Phase 1: Applicants of Database Capabilities.
        • Data modeling / design
        • Data storage & operation
        • Data security
        • Data integration and interoperability
      • 3.4.2. Phase 2: Data Quality
        • Metadata
        • Data Architecture
      • 3.4.3. Phase 3: Data Governance
        • Document and Content Management
        • Reference Data Management
        • Master Data Management
        • Data Warehousing & Business Intelligence
      • 3.4.4. Phase 4: Advanced Practices
        • Data Mining Analytics
        • Big Data
      • 3.4.5. Aiken’s pyramid draws from the DAMA Wheel, but also informs it by showing the relation between the Knowledge Areas. They are not all interchangeable; they have various kinds of interdependencies. The Pyramid framework has two drivers. First, the idea of building on a foundation, using components that need to be in the right places to support each other. Second, the somewhat contradictory idea that these may be put in place in an arbitrary order.
    • 3.5. DAMA Data Management Framework Evolved
      • 3.5.1. DAMA Functional Area Dependencies
        • 
      • 3.5.2. DAMA Data Management Function Framework
        • 
      • 3.5.3. DAMA Wheel Evolved
        • 
    • take the DAMA Wheel as a starting point and rearrange the pieces in order to betterunderstand and describe the relationships between them.
  • 4. DAMA and the DMBOK
    • 4.1. Mission
      • 4.1.1. Providing a functional framework
      • 4.1.2. Establishing a common vocabulary
      • 4.1.3. Serving as the fundamental reference guide for the CDMP
    • 4.2. Structure
      • 4.2.1. Introduction 引言
        • Business Drivers 业务驱动因素
        • Goals and Principles 目标和原则
        • Essential Concepts 基本概念
      • 4.2.2. Activities 活动
      • 4.2.3. Tools 工具
      • 4.2.4. Techniques 方法
      • 4.2.5. Implementation Guidelines 实施指南
      • 4.2.6. Relation to Data Governance 与数据治理的关系
      • 4.2.7. Metrics 度量指标
    • 4.3. Content
      • 4.3.1. (Chapter 3). Data Governance provides direction and oversight for data management by establishing a system of decision rights over data that accounts for the needs of the enterprise.
        • 建章立制，对管理的管理
        • 26. Scope and priorities management in a data governance program is a process of A：proactive change management B：responding to changes in the business environment that are often unanticipated 不可预料的 C：responding to rapid shifts 快速转变 in stakeholders and stakeholder interests. D：predicting volatile 不稳定 business environments while maintaining static data E：none 正确答案：D 你的答案：B 解析：预测不稳定的业务，同时维护静态稳定数据，这样能做好范围和优先级管理。
      • 4.3.2. (Chapter 4). Data Architecture defines the blueprint for managing data assets by aligning with organizational strategy to establish strategic data requirements and designs to meet these requirements.
        • 规划组织的数据蓝图
      • 4.3.3. (Chapter 5). Data Modeling and Design is the process of discovering, analyzing, representing, and communicating data requirements in a precise form called the data model.
        • 没有建模就没有数据
      • 4.3.4. (Chapter 6). Data Storage and Operations includes the design, implementation, and support of stored data to maximize its value. Operations provide support throughout the data lifecycle from planning for to disposal of data.
        • 业务连续性的关键
      • 4.3.5. (Chapter 7). Data Security ensures that data privacy and confidentiality are maintained, that data is not breached, and that data is accessed appropriately.
        • 安全是一种高级竞争力
      • 4.3.6. (Chapter 8). Data Integration and Interoperability includes processes related to the movement and consolidation of data within and between data stores, applications, and organizations.
        • 对数据移动进行有效管理
      • 4.3.7. (Chapter 9). Document and Content Management includes planning, implementation, and control activities used to manage the lifecycle of data and information found in a range of unstructured media, especially documents needed to support legal and regulatory compliance requirements.
        • 管理非结构化数据
      • 4.3.8. (Chapter 10). Reference and Master Data includes ongoing reconciliation and maintenance of core critical shared data to enable consistent use across systems of the most accurate, timely, and relevant version of truth about essential business entities.
        • 数据之源
      • 4.3.9. (Chapter 11). Data Warehousing and Business Intelligence includes the planning, implementation, and control processes to manage decision support data and to enable knowledge workers to get value from data via analysis and reporting.
        • 数据价值提供者
        • 1. Decision making using the collection，integration and presentation of facts is A：business intelligence B：executive analysis C：enterprise reporting D：enterprise information management reporting E：Machine Learning 正确答案：A 你的答案：D 解析：（9）数据仓库和商务智能（Data Warehousing and Business Intelligence） 包括计划、实施和控制流程来管理决策支持数据，并使知识工作者通过分析报告从数据中获得价值（参见第11章）。
      • 4.3.10. (Chapter 12). Metadata includes planning, implementation, and control activities to enable access to high quality, integrated Metadata, including definitions, models, data flows, and other information critical to understanding data and the systems through which it is created, maintained, and accessed.
        • 关于数据的数据
      • 4.3.11. (Chapter 13). Data Quality includes the planning and implementation of quality management techniques to measure, assess, and improve the fitness of data for use within an organization.
        • 有质量才有价值
      • 4.3.12. (Chapter 2) Data Handling Ethics describes the central role that data ethics plays in making informed, socially responsible decisions about data and its uses. Awareness of the ethics of data collection, analysis, and use should guide all data management professionals.
      • 4.3.13. (Chapter 14.) Big Data and Data Science describes the technologies and business processes that emerge as our ability to collect and analyze large and diverse data sets increases.
      • 4.3.14. (Chapter 15) Data Management Maturity Assessment outlines an approach to evaluating and improving an organization’s data management capabilities.
      • 4.3.15. (Chapter 16) Data Management Organization and Role Expectations provide best practices and considerations for organizing data management teams and enabling successful data management practices.
      • 4.3.16. (Chapter 17) Data Management and Organizational Change Management describes how to plan for and successfully move through the cultural changes that are necessary to embed effective data management practices within an organization.
  • 5. Works Cited / Recommended 文献引用与推荐
    • 5.1. 9. Transparent data management processes provide A：the right data to meet business information needs B：surprise goals,metrics and monitoring C：the elimination of data redundancy waste and rework. D：no black-box data management activities and fewer surprises E：all 正确答案：D 你的答案：E 解析：Transparent 没有黑盒
    • 5.2. 15. When outsourcing information management functions，organizations can__. A：lmprove controls while reducing costs B：Transfer control but not accountability 转移操作，留下责任 C：Transfer accountability but not control 转移责任，留下操作 D：Reduce cost of compliance and improve turnaround 提升了转机 E：Align strategy and control privacy 正确答案：B 你的答案：C 解析：转移了控制权而非负责，责任仍在企业组织
    • 5.3. 12. The main benefits of data stewardship are A：consistent use of data management resources，improved Bl deployment success rate s, and lower migration costs. B：improved data resource management，more effective data storage management and lower migration costs C：improved master data management deployment success rates easy data mapping， and lower SOA cost of ownership D：consistent use of data management resources，easy data mapping，and lower migration costs E：all 正确答案：E 你的答案：E 解析：1.1等：信息和知识是竞争优势的关键。拥有关于客户、产品、服务和运营的可靠、高质量数据的组织，能够比没有数据或数据不可靠的组织做出更好的决策。如果不能像管理资本一样管理好数据，就会浪费和失去机会。正如有效管理财务和物理资产使组织能够从这些资产中获取价值一样，数据管理的主要驱动力也是使组织能够从其数据资产中获取价值。
    • 5.4. 20. Typical types of assessments used to describe an organizations state of information management capability do not include A：Business Alignment B：Capacity to Change C：Security and Penetration Testing 渗透测试 D：Collaborative Readiness E：Data Management Maturity 正确答案：C 你的答案：C 解析：C是数据安全中的一项测试技术，非成熟度评估
• Chapter 2: Data Handling Ethics 数据处理伦理
  • 
  • 1. Introduction
    • 1. Definition:
      • ethics are principles of behavior based on ideas of right and wrong
      • Ethical principles often focus on ideas such as fairness, respect, responsibility, integrity, quality, reliability, transparency, and trust.
      • Unethical data handling can result in the loss of reputation and customers,
      • Core concepts:
        • 1. Impact on people
          • Because data represents characteristics of individuals and is used to make decisionsthat affect people’s lives, there is an imperative to manage its quality and reliability.
        • 2. Potential for misuse
          • Misusing data can negatively affect people and organizations, so there is an ethicalimperative to prevent the misuse of data
        • 3. Economic value of data
          • Data has economic value. Ethics of data ownership should determine how thatvalue can be accessed and by whom.
        • 4. 6. which of these are increasingly driving legislation 立法 for information security and data privacy? A：recognition of Ethical issues 伦理问题 in information management B：A desire for economic protectionism C：An objective of making life more challenging for information management professionals D：GDPR1 E：A resistance 抵制 to open data and transparency 正确答案：A 你的答案：A 解析：2.1题解：数据处理伦理问题较为复杂，不过主要集中在几个核心概念上：1）对人的影响。由于数据代表个人的特征，可被用于各类决策，从而影响人们的生活，因此必须保证其质量和可靠性。2）滥用的可能。滥用数据会对人和组织造成负面影响，所以需要有伦理准则来防止数据被滥用。3）数据的经济价值。数据存在经济价值。需要规定数据所有权，即谁可以去使用数据及如何使用数据。组织保护数据的动机很大程度上来自法律法规的要求。然而，由于数据代表了人（客户、员工、患者、供应商等），数据管理专业人员应认识到，保护数据并且确保其不被滥用除了法律约束以外还有伦理因素。即使不直接代表个人的数据也可能会用于做出影响人们生活的决策。
      • Data handling ethics are concerned with how to procure, store, manage, interpret, analyze / apply and dispose of data in ways that are aligned with ethical principles,including community responsibility.
    • 2. Goals:
      • 1. To define ethical handling of data in the organization.
      • 2. To educate staff on the organization risks of improper data handling.
      • 3. To change/instill preferred culture and behaviors on handling data.
      • 4. To monitor regulatory environment, measure, monitor, and adjust organization approaches for ethics in data.
  • 2. Business Drivers
    • 2.1. Like W. Edward Deming’s statements on quality, ethics means “doing it right when no one is looking.” An ethical approach to data use is increasingly being recognized as a competitive business advantage
      • 2.1.1. 5. One way of defining ethics is: A：doing it wrong and failing to covering it up B：doing it right when someone is looking C：doing it wrong,and then expertly covering it up D：doing it wrong and then apologizing E：doing it right when no one is looking 在没人注意的时候做正确的事儿。 正确答案：E 你的答案：E 解析：暂无解析
    • 2.2. Ethical data handling can increase the trustworthiness of an organization and the organization’s data and process outcomes. This can create better relationships between the organization and its stakeholders.
    • 2.3. Reducing the risk that data for which the organization is responsible will be misused by employees, customers, or partners is a primary reason for an organization to cultivate ethical principles for data handling.
    • 2.4. There is also an ethical responsibility to secure data from criminals (i.e., to protect against hacking and potential data breaches
    • 2.5. Different models of data ownership influence the ethics of data handling. For example, technology has improved the ability of organizations to share data with each other. This ability means organizations need to make ethical decisions about their responsibility for sharing data that does not belong to them.
    • 2.6. The emerging roles of Chief Data Officer, Chief Risk Officer, Chief Privacy Officer, and Chief Analytics Officer are focused on controlling risk by establishing acceptable practices for data handling. But responsibility extends beyond people in these roles. Handling data ethically requires organization-wide recognition of the risks associated with misuse of data and organizational commitment to handling data based on principles that protect individuals and respect the imperatives related to data ownership.
  • 3. Essential Concepts
    • 3.1. Ethical Principles for Data
      • 3.1.1. Respect for Persons
        • This principle reflects the fundamental ethical requirement that people be treated in a way that respects their dignity and autonomy as human individuals. It also requires that in cases where people have 'diminished autonomy', extra care be taken to protect their dignity and rights.
      • 3.1.2. Beneficence
        • This principle has two elements: first, do not harm; second, maximize possible benefits and minimize possible harms.
      • 3.1.3. Justice
        • This principle considers the fair and equitable treatment of people.
      • US-HSS,1979
      • 3.1.4. Respect for Law and Public Interest
      • US-DHS,2012
      • 3.1.5. Future-oriented regulation of data processing and respect for the rights to privacy and to data protection
      • 3.1.6. Accountable controllers who determine personal information processing
      • 3.1.7. Privacy conscious engineering and design of data processing products and services
      • 3.1.8. Empowered individuals
      • EDPS,2015
      • 3.1.9. 7. The needs of data protection require us to ensure that.. A：Data is secured with a password B："Data is processed only in ways compatible with the intended and communicated use it was collected for, and respects the consent 同意 of the data subject" C：Data is encrypted at all times D：Data can always be freely used in the company as it is a company asset E：Data is frequently backed up so that it can be recovered in all cases 正确答案：B 你的答案：B 解析：2.3.1. 题解：2015年，欧盟数据保护主管发表了一篇关于数字伦理方面的文章，强调了关于数据处理和大数据发展的“工程、哲学、法律和伦理含义”，呼呼关注维护人类尊严的数据处理，并明确提出了信息生态系统中数据处理伦理所必须遵循的四大支柱（EDPS，2015），即1）面向未来的数据处理条例、尊重隐私权和数据保护权利。2）确定个人信息处理的责任人。3）数据处理产品及服务设计及工程过程中的隐私意识。4）增加个人的自主权。这些准则大致符合贝尔蒙报告中提出的准则，旨在提升人类尊严和自主权。
    • 3.2. Principles Behind Data Privacy Law
      • 3.2.1. Privacy law is not new. Privacy and information privacy as concepts are firmly linked to the ethical imperative to respect human rights. In 1890, American legal scholars Samuel Warren and Louis Brandeis described privacy and information privacy as human rights with protections in common law that underpin several rights in the US constitution. In 1973, a code of Fair Information Practice was proposed, and the concept of information privacy as a fundamental right was reaffirmed in the US Privacy Act of 1974, which states that “the right to privacy is a personal and fundamental right protected by the Constitution of the United States”.
      • 3.2.2. The OECD principles have since been superseded by principles underlying the General Data Protection Regulation of the EU, (GDPR, 2016).
      • 3.2.3. GDPR, 2016
        • Fairness, Lawfulness, Transparency
          • Personal data shall be processed lawfully, fairly, and in a transparent manner in relation to the data subject.
        • Purpose Limitation
          • Personal data must be collected for specified, explicit, and legitimate purposes, and not processed in a manner that is incompatible with those purposes.
        • Data Minimization
          • Personal data must be adequate, relevant, and limited to what is necessary in relation to the purposes for which they are processed.
        • Accuracy
          • Personal data must be accurate, and where necessary, kept up-to-date. Every reasonable step must be taken to ensure that personal data that are inaccurate, having regard to the purpose for which they are processed, are erased or rectified without delay.
        • Storage Limitation
          • Data must be kept in a form that permits identification of data subjects [individuals] for no longer than is necessary for the purposes for which the personal data are processed.
        • Integrity and Confidentiality
          • Data must be processed in a manner that ensures appropriate security of the personal data, including protection against unauthorized or unlawful processing and against accidental loss, destruction or damage, using appropriate technical or organizational measures.
        • Accountability
          • Data Controllers shall be responsible for, and be able to demonstrate compliance with [these principles].
        • 3. In a multinational corporation that manages global data. it is likely that you'll need （）Data stewards A：subject area B：unit C：project D：location-oriented E：program 正确答案：D 你的答案：D 解析：2.3.2.需要本地化数据管理专员。欧盟立法标准制定后，增强对个人隐私保护的立法，已成为全球趋势。世界各地法律对于跨国界的流动有不同类型的限制。即使在跨国公司内部，在全球范围内共享数据都受到法律限制。因此，重要的是组织制定制度和指导方针，使员工能够遵守相关法律要求，并在组织的风险偏好范围内使用数据。
      • 3.2.4. PIPEDA
        • Accountability
          • An organization is responsible for personal information under its control and must designate an individual to be accountable for the organization's compliance with the principle.
        • Identifying Purposes
          • An organization must identify the purposes for which personal information is collected at or before the time the information is collected.
        • Consent
          • An organization must obtain the knowledge and consent of the individual for the collection, use, or disclosure of personal information, except where inappropriate.
        • Limiting Collection, Use, Disclosure, and Retention
          • The collection of personal information must be limited to that which is necessary for the purposes identified by the organization. Information shall be collected by fair and lawful means. Personal information shall not be used or disclosed for purposes other than those for which it was collected, except with the consent of the individual or as required by law. Personal information shall be retained only as long as necessary for the fulfillment of those purposes.
          • 1. The essence of data privacy initiatives include all of the following EXCEPT A：use B：collection C：integrity D：disclosure 披露 E：No answer 正确答案：E 你的答案：E 解析：2.3.2.于PIPEDA的法定义务
          • 2. ldentify who has primary responsibility for data capture 数据采集 and usage design within programs A：Software Architects, Developers B：Suppliers, Consumers C：DM Executive 数据挖掘，Bi Analysts，data Security Administrator D：Business Data Stewards, Subject Matter Experts (SMEs) E：Data Architects，Data Analysts Database Administrators 正确答案：A 你的答案：D 解析：针对数据采集。B都不对，C BI不对 D Stewards不对，E Administrator不对，排除法
        • Accuracy
          • Personal information must be as accurate, complete, and up-to-date as is necessary for the purposes for which it is to be used.
        • Safeguards
          • Personal information must be protected by security safeguards appropriate to the sensitivity of the information.
        • Openness
          • An organization must make specific information about its policies and practices relating to the management of their personal information readily available to individuals.
        • Individual Access
          • Upon request, an individual shall be informed of the existence, use, and disclosure of his or her personal information, and shall be given access to that information. An individual shall be able to challenge the accuracy and completeness of the information and have it amended as appropriate.
        • Compliance Challenges
          • An individual shall be able to address a challenge concerning compliance with the above principles to the designated individual or individuals accountable for the organization's compliance.
      • 3.2.5. FTC, 2012
        • Notice / Awareness
          • Data collectors must disclose their information practices before collecting personal information from consumers.
        • Choice / Consent
          • Consumers must be given options with respect to whether and how personal information collected from them may be used for purposes beyond those for which the information was provided.
        • Access / Participation
          • Consumers should be able to view and contest the accuracy and completeness of data collected about them.
        • Integrity / Security
          • Data collectors must take reasonable steps to assure that information collected from consumers is accurate and secure from unauthorized use.
        • Enforcement / Redress
          • The use of a reliable mechanism to impose sanctions for noncompliance with these fair information practices.
      • 3.2.6. Others
        • Simplified consumer choice to reduce the burden placed on consumers
        • The recommendation to maintain comprehensive data management procedure throughout the information lifecycle
        • Do Not Track option
        • Requirements for affirmative express consent
        • Concerns regarding the data collection capabilities of large platform providers; transparency and clear privacy notices and policies
        • Individuals' access to data
        • Educating consumers about data privacy practices
        • Privacy by Design
      • 3.2.7. There is a global trend towards increasing legislative protection of individuals’ information privacy, following the standards set by EU legislation. Laws around the world place different kinds of restrictions on the movement of data across international boundaries. Even within a multinational organization, there will be legal limits to sharing information globally. It is therefore important that organizations have policies and guidelines that enable staff to follow legal requirements as well as use data within the risk appetite of the organization.
    • 3.3. Online Data in an Ethical Context
      • 3.3.1. Ownership of data
        • The rights to control one's personal data in relation to social media sites and data brokers. Downstream aggregators of personal data can embed data into deep profiles that individuals are not aware of.
      • 3.3.2. The Right to be Forgotten
        • To have information about an individual be erased from the web, particularly to adjust online reputation. This topic is part of data retention practices in general.
      • 3.3.3. Identity
        • Having the right to expect one identity and a correct identity, and to opt for a private identity.
      • 3.3.4. Freedom of speech online
        • Expressing one's opinions versus bullying, terror inciting, 'trolling,' or insulting
    • 3.4. Risks of Unethical Data Handling Practices
      • 3.4.1. The classic book How to Lie with Statistics by Darrell Huff (1954) describes a range of ways that data can be used to misrepresent facts while creating a veneer of factuality. Methods include judicious data selection, manipulation of scale, and omission of some data points. These approaches are still at work today.
      • 3.4.2. Timing 时机的选择
        • It is possible to lie through omission 遗漏 or inclusion 包含 of certain data points in a report or activity based on timing.
      • 3.4.3. Misleading Visualizations 可视化误导
        • Charts and graphs can be used to present data in a misleading manner.
      • 3.4.4. Unclear Definitions or Invalid Comparisons 定义不清晰或无效的比较
      • 3.4.5. Bias 偏见
        • Bias refers to an inclination of outlook. 倾向性的观点
        • Types
          • Data Collection for pre-defined result 预设结论的数据采集
          • Biased use of data collected 偏见的数据采集
          • Hunch and search 预感和搜索
          • Biased sampling methodology 片面抽样方法
          • Context and Culture 背景和文化
      • 3.4.6. Transforming and Integrating Data 转换和集成数据
        • Limited knowledge of data's origin and lineage 数据来源和血缘了解有限
        • Data of poor quality 质量差的数据
        • Unreliable Metadata 不可靠的元数据
        • No documentation of data remediation history 没有数据修订历史的文档
      • 3.4.7. Obfuscation / Redaction of Data 数据的混淆与修订
        • Data aggregation 数据聚合
          • When aggregating data across some set of dimensions, and removing identifying data, a dataset can still serve an analytic purpose without concern for disclosing personal identifying information (PII). Aggregations into geographic areas are a common practice (see Chapters 7 and 14).
        • Data marking 数据标记
          • Data marking is used to classify data sensitivity (secret, confidential, personal, etc.) and to control release to appropriate communities such as the public or vendors, or even vendors from certain countries or other community considerations.
        • Data masking 数据脱敏
          • Data masking is a practice where only appropriate submitted data will unlock processes. Operators cannot see what the appropriate data might be; they simply type in responses given to them, and if those responses are correct, further activities are permitted. Business processes using data masking include outsourced call centers, or sub-contractors who should only have partial access to information
    • 3.5. Establishing an Ethical Data Culture
      • 3.5.1. Review Current State Data Handling Practices
      • 3.5.2. Identify Principles, Practices, and Risk Factors
      • 3.5.3. Create an Ethical Data Handling Strategy and Roadmap
        • 1. Values statements
        • 2. Ethical data handling principles
        • 3. Compliance framework
        • 4. Risk assessments
        • 5. Training and communications
        • 6. Roadmap
        • 7. Approach to auditing and monitoring
      • 3.5.4. Adopt a Socially Responsible Ethical Risk Model
        • 4. In data handling ethics，'social licence' refers to the alignment between A：stakeholder demands and technology deliverables B：society , 's needs and their right to access data C：stakeholder expectations and the organization D：social and political decision matrices E：public perception 公共认知 and published fact 正确答案：E 你的答案：D 解析：认知与现实对齐，公序良俗
        • Ethical Risk Model for Sampling Projects 抽样项目的伦理风险模型
          • 
          • How they select their populations for study (arrow 1)
          • How data will be captured (arrow 2)
          • What activities analytics will focus on (arrow 3)
          • How the results will be made accessible (arrow 4)
    • 3.6. Data Ethics and Governance
      • 3.6.1. Oversight for the appropriate handling of data falls under both data governance and legal counsel. Together they are required to keep up-to-date on legal changes, and reduce the risk of ethical impropriety by ensuring employees are aware of their obligations. Data Governance must set standards and policies for and provide oversight of data handling practices.
      • 3.6.2. DAMA International's Certified Data Management Professional (CDMP) certification requires that data management professional subscribe to a formal code of ethics, including an obligation to handle data ethically for the sake of society beyond the organization that employs them.
  • 4. Works Cited / Recommended
• Chapter 3: Data Governance 数据治理
  • 
  • 1. Introduction
    • 1.1. Data Governance (DG) is defined as the exercise of authority and control (planning, monitoring, and enforcement) over the management of data assets.
      • 
      • 1.1.1. The purpose of Data Governance is to ensure that data is managed properly, according to policies and best practices
      • 1.1.2. While the driver of data management overall is to ensure an organization gets value out of its data
      • 1.1.3. Just as an auditor controls financial processes but does not actually execute financial management, data governance ensures data is properly managed without directly executing data management (see Figure 15). Data governance represents an inherent separation of duty between oversight and execution.
      • 1.1.4. Scope
        • 1. Strategy 战略
          • Defining, communicating, and driving execution of Data Strategy and Data Governance Strategy
        • 2. Policy 制度
          • Setting and enforcing policies related to data and Metadata management, access, usage, security, and quality
          • 31. A best practice is that data policies must apply to A：the true value of business data B：clear ownership of the data C：various business silos D：the business as a whole 整个业务 E：all 正确答案：D 你的答案：A 解析：D更合理全面，BEST
          • 46. Policies in data governance are used A：to develop those that are harder to violate than to apply 开发更难违反的 B：to develop the rules under which standards apply. 指定标准规则 C：to make standards durable and enforceable. 使标注持久可执行 D：as procedures and processes for implementing exceptions 异常处理 E：none 正确答案：C 你的答案：D 解析：C符合Polices的性质 a course or principle of action adopted or proposed by a government，party. business，or individual. Policy is a deliberate（深思熟虑）system of guidelines to guide decisions and achieve rational outcomes.
        • 3. Standards and quality 标准与质量
          • Setting and enforcing Data Quality and Data Architecture standards
          • 13. ln data governance, the key consideration for data is A：accuracy B：value C：timeliness D：quality E：all 正确答案：D 你的答案：E 解析：3.1：数据治理项目的范围和焦点依赖于组织需求，但多数项目都包含如下内容：1）战略（Strategy）。定义、交流和据动数据战略和数据治理战略的执行。2）制度（Policy），设置与数据、元数据管理、访问、使用、安全和质量有关的制度。3）标准和质量（Standards and Quality）。设置和强化数据质量、数据架构标准。4）监督（Oversight），在质量、制度和数据管理的关键领域提供观察、审计和纠正等措施（通常称为管理职责Stewardship）.5）合规（Compliance）.确保组织可以达到数据相关的监管合规性要求。6）问题管理（lssue Management）.识别、定义、升级和处理问题，针对如下领域：数据安全、数据访问、数据质量、合规、数据所有权、制度、标准、术语或者数据治理程序等。
        • 4. Oversight 监督
          • Providing hands-on observation, audit, and correction in key areas of quality, policy, and data management (often referred to as stewardship)
        • 5. Compliance 合规
          • Ensuring the organization can meet data-related regulatory compliance requirements
          • 60. Every enterprise is subject to 受制于many governmental and industry regulations many of which regulate how data and information is used and managed part of the data governance function A：Monitor and ensure that organizations meet any regulatory compliance requirements B：This is about data，data governmance is accountable for the whole process with Risk and audit reporting to DG C：Enforce enterprise-wide mandatory compliance to regulation D：Perform ad-hoc audits of possible regulations to report to the DG council on an information only basis E：This is a risk and audit responsibility Data Governance plays no role in this. 正确答案：A 你的答案：A 解析：3.1
          • 62. when new governmental and industry regulations are formulated and enacted，Data Governance plays a key role in the process of identifying the data and information components for compliance. What do you see as their most important role in any regulatory compliance project? A："Working with business and technical leadership to find the best answers to a standard set of regulatory compliance questions (How, why, When, etc) " B：Take no part in any project at all declaring it an audit and risk project C：create a DG in-house project with a team of data stewards to create a standard response D：work in isolation and mine the data and information for compliance and non-compliance issues E：Provide access to any possible data set to the compliance team and allow them to mine the data for non-compliance 正确答案：A 你的答案：A 解析：components for compliance与业务和技术领导合作，找到一组标准法规遵从性问题（如何，为什么，何时等）的最佳答案”
        • 6. Issue management 问题管理
          • Identifying, defining, escalating, and resolving issues related to data security, data access, data quality, regulatory compliance, data ownership, policy, standards, terminology, or data governance procedures
        • 7. Data management projects 数据管理项目
          • Sponsoring efforts to improve data management practices
        • 8. Data asset valuation 数据资产估值
          • Setting standards and processes to consistently define the business value of data assets
      • 1.1.5. To accomplish these goals, a Data Governance program will develop policies and procedures, cultivate data stewardship practices at multiple levels within the organization, and engage in organizational change management efforts that actively communicate to the organization the benefits of improved data governance and the behaviors necessary to successfully manage data as an asset.
      • 1.1.6. For most organizations, adopting formal Data Governance requires the support of organizational change management (see Chapter 17), as well as sponsorship from a C-level executive, such as Chief Risk Officer, Chief Financial Officer, or Chief Data Officer.
      • 1.1.7. 3. Data governance requires consideration of the following A：Issues, Policies Standards，Strategy validation Organization roles projects Services B：Strategy, Enterprise Data Modeling, Value Chain Analysis and Measurement. C：Architecture, Integration, Control and Delivery D：Standards, Classification, Administration, Authentication and Auditing E：None 正确答案：A 你的答案：B 解析：3.1：数据治理项目的范围和焦点依赖于组织需求，但多数项目都包含如下内容：1）战略（Strategy）。定义、交流和驱动数据战略和数据治理战略的执行。2）制度（Policy）。设置与数据、元数据管理、访问、使用、安全和质量有关的制度。3）标准和质量（Standards and Quality）.设置和强化数据质量、数据架构标准。4）监督（Oversight）。在质量、制度和数据管理的关键领域提供观察、审计和纠正等措施（通常称为管理职责Stewardship）。5）合规（Compliance）.确保组织可以达到数据相关的监管合规性要求。6）问题管理（（lssue Management）。识别、定义、升级和处理问题
      • 1.1.8. 4. Data governance scope includes all EXCEPT A：regulatory compliance. B：communication C：security enforcement. D：data standards and architecture E：Stewardship. 正确答案：C 你的答案：D 解析：同上，质量增强，非安全增强
      • 1.1.9. 14. Data Governance team roles include all of the following EXCEPT A：CIO B：CFO/CEO C：Chief data officer. D：data modelers E：Data owner 正确答案：B 你的答案：A 解析：见语境关系图
      • 1.1.10. 16. The process aspect of Data Governance includes all of the following EXCEPT A：policies B：rules. C：access privileges 访问特权 D：procedures E：procedures 正确答案：C 你的答案：C 解析：C是权限不是流程，性质不对
      • 1.1.11. 17. Authority in a data governance program is implemented through A：autonomous informed and influential management style B：high scope decisions made based on high quality data C：designated decision rights 指定决策权 based on data management policy D：executive sponsorship and delegation of authority. E：all 正确答案：C 你的答案：C 解析：C和题干意思对应
      • 1.1.12. 35. To treat Data Governance in the enterprise as___ is a misconception A：a change B：re-engineering 再造 C：a framework D：A project E：A program 正确答案：D 你的答案：B 解析：数据治理（Data Governance，DG）的定义是在管理数据资产过程中行使权力和管控，包括计划、监控和实施。数据治理并不是项目。
      • 1.1.13. 44. Data governance differs from IT governance in that A：serious problems can occur in the project cycle, and after operationalized versus up front features analysis and design in technology projects B：Serious problems can be discovered at any level of the organization versus top-down dentification of risks and issues in technology C：you buy and deploy solutions at increasing levels of specification through the project D：no single group has control of data as it flows throughout the organization versus single owner assignment of technology. E：None 正确答案：D 你的答案：D 解析：正确答案：D来源：3.1.1题解：只有D提到了数据。 数据治理要与IT治理区分开。IT治理制定关于IT投资、IT应用组合和IT项目组合的决策，从另一个角度还包括硬件、软件和总体技术架构。IT治理的作用是确保IT战略、投资与企业目标、战略的一致性。COBIT（Control Objectives for Information and Related Technology）框架提供IT治理标准，但是其中仅有很少部分涉及数据和信息管理。其他一些重要法规，如萨班斯法案（Sarbanes-Oxley）则覆盖企业治理、IT治理和数据治理多个领域。相反，数据治理仅聚焦于管理数据资产和作为资产的数据。
      • 1.1.14. 79. Data governance treats data as A：an enterprise capital asset. B：poor quality and in need of continuous improvement. C：a collection of information D：a critical element of the business that cannot be managed E：all 正确答案：A 你的答案：A 解析：3.1. 题解：数据治理（Data Governance，DG）的定义是在管理数据资产过程中行使权力和管控，包括计划、监控和实施。在所有组织中，无论是否有正式的数据治理职能，都需要对数据进行决策。建立了正式的数据治理规程及有意向性地行使权力和管控的组织，能够更好地增加从数据资产中获得的收益。
    • 1.2. Business Drivers
      • 1.2.1. Drivers
        • 1. The most common driver for data governance is often regulatory compliance, especially for heavily regulated industries, such as financial services and healthcare. Responding to evolving legislation requires strict data governance processes. The explosion in advanced analytics and Data Science has created an additional driving force.
        • 2. While compliance or analytics may drive governance, many organizations back into data governance via an information management program driven by other business needs, such as Master Data Management (MDM), by major data problems, or both. A typical scenario: a company needs better customer data, it chooses to develop Customer MDM, and then it realizes successful MDM requires data governance.
        • 3. Data governance is not an end in itself. It needs to align directly with organizational strategy. The more clearly it helps solve organizational problems, the more likely people will change behaviors and adopt governance practices. Drivers for data governance most often focus on reducing risks or improving processes.
        • 4. 42. Data governance program business drivers include all of the following EXCEPT A：regulation compliance B：hot site deployment 热站点部署 C：maximize profit D：designated terrorist 指定恐怖分子 access control E：all 正确答案：B 你的答案：D 解析：B是站点部署与数据治理无关
      • 1.2.2. Reducing Risk
        • 1. General risk managemen
          • Oversight of the risks data poses to finances or reputation, including response to legal (E-Discovery) and regulatory issues.
          • 38. ln data governance risk management，what are the most appropriate risk responses that management can choose? A：Acknowledge，mitigate 减轻, transfer or accept the risk B：Acknowledge，transfer，mitigate or eliminate the risk C：Conduct a threat assessment calculate the impact of the threat and evaluate the control measures D：Accept, mitigate，transfer or deny the risk E：all 正确答案：D 你的答案：C 解析：D更复合逻辑语言
        • 2. Data security
          • Protection of data assets through controls for the availability, usability, integrity,consistency, auditability and security of data.
        • 3. Privacy
          • Control of private / confidential / Personal Identifying Information (PII) through policy and compliance monitoring
          • 41. Data governance policy alignment in the private sector begins with all of the following EXCEPT A：establishing controls necessary to assure compliance B：understand regulations that drive policy. C：identify data management policies D：understand goals and purpose of each policy. E：all 正确答案：A 你的答案：A 解析：private和compliance（合规）一般是外部的，逻辑不对
        • 4. 45. Data quality and risk management are strongly connected to A：teamwork facilitation and consensus building 建立共识 B：business requirements for data and information helps to set priorities and maintain a roadmap of activities to meet requirements. C：business requirements for data and information D：goals of and motivations for data governance E：None 正确答案：D 你的答案：C 解析：题解：数据治理的驱动因素大多聚焦于减少风险或者改进流程。（1）减少风险1）一般性风险管理。洞察风险数据对财务或商誉造成的影响，包括对法律（电子举证E-Discovery）和监管问题的响应。2）数据安全。通过控制活动保护数据资产，包括可获得性、可用性、完整性、连续性、可审计和数据安全。3）隐私。通过制度和合规性监控，控制私人信息、机密信息、个人身份信息（PlI）等。（2）改进流程1）法规遵从性。有效和持续地响应监管要求的能力。2）数据质量提升。通过真实可信的数据提升业务绩效的能力。
      • 1.2.3. Improving Processes
        • 1. Regulatory compliance
          • The ability to respond efficiently and consistently to regulatoryrequirements.
        • 2. Data quality improvement
          • ability to contribute to improved business performance bymaking data more reliable.
        • 3. Metadata Management
          • Establishment of a business glossary to define and locate data in theorganization; ensuring the wide range of other Metadata is managed and made available to theorganization.
        • 4. Efficiency in development projects
          • SDLC improvements to address issues and opportunities indata management across the organization, including management of data-specific technical debtthrough governance of the data lifecycle.
        • 5. Vendor management
          • Control of contracts dealing with data, such as cloud storage, externaldata purchase, sales of data as a product, and outsourcing data operations
      • 1.2.4. Data governance is separate from IT governance. IT governance makes decisions about IT investments, the IT application portfolio, and the IT project portfolio – in other words, hardware, software, and overall technical architecture. IT governance aligns the IT strategies and investments with enterprise goals and strategies.
        • 56. which of these does not characterize an effective data steward? A：ls a highly experienced technical expert in a variety of data management disciplines tools B：He/she is an effective communicator C：He/she works collaboratively across the organization with data stakeholders and others ldentifying data problems issues D：He/she works in association with the data Owner to protect and enhance the data assets under his or her control E：ls a recognized subject matter expert in the data subject area/business domain that he or she is responsible for 正确答案：A 你的答案：D 解析：A是DBA的特点，不是数据管家.
      • 1.2.5. COBIT (Control Objectives for Information and Related Technology) framework provides standards for IT governance, but only a small portion of the COBIT framework addresses managing data and information. Some critical topics, such as Sarbanes-Oxley compliance (U.S.A.), span the concerns of corporate governance, IT governance, and data governance. In contrast, Data Governance focuses exclusively on the management of data assets and of data as an asset.
        • 2. The Control objectives for Information and related Technology (CobiT) addresses A：Data governance B：IT Governance C：IT project portfolio. D：IT Investments E：none 正确答案：B 你的答案：B 解析：正确答案：B来源：3.1.1题解： 数据治理要与IT治理区分开。IT治理制定关于IT投资、IT应用组合和IT项目组合的决策，从另一个角度还包括硬件、软件和总体技术架构。IT治理的作用是确保IT战略、投资与企业目标、战略的一致性。COBIT（Control Objectives for Information and Related Technology）框架提供IT治理标准，但是其中仅有很少部分涉及数据和信息管理。其他一些重要法规，如萨班斯法案（Sarbanes-Oxley）则覆盖企业治理、IT治理和数据治理多个领域。相反，数据治理仅聚焦于管理数据资产和作为资产的数据。
      • 1.2.6. Data governance is not a one-time thing.
    • 1.3. Goals and Principles
      • 1.3.1. The goal of Data Governance is to enable an organization to manage data as an asset.
        • 1. Sustainable 可持续发展
          • It does mean managing change in a way that is sustainable beyond the initial implementation of any data governance component.
          • 73. The goal of data govermance is to enable an organization to manage data as an asset To achieve this，the DG programs must be A：able to register the data asset with the financial controller to ensure it is managed like all other assets B：able to assign a dollar value to a data asset in order to determine the appropriate cos t-toinvestment ratio for budgeting purposes C：fixed to achieve a successful outcome in a defined time period D：sustainable，to be created as an ongoing practice with leadership sponsorship and ownership E：represented by finance during the process for acquiring and disposing of the data asse 正确答案：D 你的答案：D 解析：3.1.2. 题解：（1）可持续发展（Sustainable）治理程序必须富有吸引力。它不是以一个项目作为终点，而是一个持续的过程。需要把它作为整个组织的责任。数据治理必须改变数据的应用和管理方式，但也不代表着组织要作巨大的更新和颠覆。数据治理是超越一次性数据治理组件实施可持续发展路径的管理变革。可持续的数据治理依靠于业务领导、发起者和所有者的支持。pr
        • 2. Embedded 嵌入式
          • DG is not an add-on process. DG activities need to be incorporated into development methods for software, use of data for analytics, management of Master Data, and risk management.
        • 3. Measured 可度量
          • DG done well has positive financial impact, but demonstrating this impact requires understanding the starting point and planning for measurable improvement.
      • 1.3.2. DG provides the principles, policy, processes, framework, metrics, and oversight to manage data as an asset and to guide data management activities at all levels.
        • 1. Goals and Principles are one of the seven basic Environment Elements of the Functional framework for data governance that includes A：Strategic Goals. Dependencies. Alternative Techniques. Reporting Structures. B：Objectives. C：Vision Mission. Business Benefits. Strategic Goals, and Specific D：Inputs outputs. Critical Success Factors. Use Case Scenarios，and Recognized Best Practices. E：All 正确答案：C 你的答案：C 解析： 3.1.2目标和原则数据治理的目标是使组织能够将数据作为资产进行管理。数据治理提供治理原则、制度、流程、整体框架、管理指标，监督数据资产管理，并指导数据管理过程中各层级的活动。
        • 8. Data governance is A：focused on developing operating, sustaining and growing the data function B：a program a set of projects and services designed to manage the data assets C：an effort that coordinates the activities of data owners and data specialists. D：used to develop and operate a set of database files and maintain a changing set of data models to create flexible and market responsive organization E：all 正确答案：C 你的答案：B 解析：3.1数据治理职能是指导所有其他数据管理领域的活动。数据治理的目的是确保根据数据管理制度和最佳实践正确地管理数据。而数据管理的整体驱动力是确保组织可以从其数据中获得价值，数据治理聚焦于如何制定有关数据的决策，以及人员和流程在数据方面的行为方式。
        • 10. Data governance provides ( ) for effective control and use of data assets A：good practices. B：management. C：a framework D：responsibility. E：A project 正确答案：C 你的答案：C 解析：3.1：数据治理（Data Governance，DG）的定义是在管理数据资产过程中行使权力和管控，包括计划、监控和实施。在所有组织中，无论是否有正式的数据治理职能，都需要对数据进行决策。建立了正式的数据治理规程及有意向性地行使权力和管控的组织，能够更好地增加从数据资产中获得的收益。
        • 33. Which one of the following is the MOST important success in implementing data Governance? A：Defining measures B：Defining scope C：ldentifying actions D：Setting goals E：all 正确答案：D 你的答案：D 解析：3.1.2：有了目标再考虑方法和进行度量，目标错了则其他无从谈起。 3.1.2目标和原则数据治理的目标是使组织能够将数据作为资产进行管理。数据治理提供治理原则、制度、流程、整体框架、管理指标，监督数据资产管理，并指导数据管理过程中各层级的活动。
        • 36. Data governance is the organization and implementation of A：rules for competitive market share analytics B：accounting and finance policies to provide accurate record keeping C：policies, procedures，structure and roles and responsibilities for managing information assets D：rights for independent action and decision making by corporate management. E：none 正确答案：C 你的答案：C 解析：数据治理（Data Governance，DG）的定义是在管理数据资产过程中行使权力和管控，包括计划、监控和实施。数据治理并不是项目。
      • 1.3.3. Principles to set a foundation for DG
        • Leadership and strategy 领导力与战略
        • Business-driven 业务驱动
        • Shared responsibility 共担责任
        • Multi-layered 多层面
        • Framework-based 基于框架
        • Principle-based 原则导向
    • 1.4. Essential Concepts
      • 1.4.1. Data-centric Organization 以数据为中心的组织
        • Data should be managed as a corporate asset
        • Data management best practices should be incented across the organization
        • Enterprise data strategy must be directly aligned with overall business strategy
        • Data management processes should be continuously improved
          • 48. Data governance business goals can be all of the following EXCEPT A：formulized 形式化 for a business sector. B：unique to the organization. C：static 静态的 D：fonnulized from best practice guidance E：Sustainable 正确答案：C 你的答案：D 解析：企业整体业务战略也不是静态的，所以治理也不是静态的。 在整个组织内澄清数据治理的业务驱动因素是基础性工作，将它与企业整体业务战略保持一致。经常聚焦“数据治理”往往会疏远那些认为治理产生额外开销却没有明显好处的领导层。对组织文化保持敏感性也是必要的，需要使用正确的语言、运营模式和项目角色。在DAMA-DMBOK2编写过程中，术语“组织"被诸如“运营模式”或“运营框架”之类所取代
      • 1.4.2. Data Governance Organization 数据治理组织
        • 
        • 1. Data Governance Steering Committee 数据治理指导委员会
          • The primary and highest authority organization for data governance in an organization, responsible for oversight, support, and funding of data governance activities. Consists of a cross-functional group of senior executives.
          • Typically releases funding for data governance and data governance-sponsored activities as recommended by the DGC and CDO. This committee may in turn have oversight from higher-level funding or initiative-based steering committees.
          • 72. The Data Governance Steering Committee is best described as: A：the local or divisional council ,working under auspices of the CDo. B：the representatives of data use on project steering committees C：the community of interest，focused on specific subject areas or projects. D：a burden to the agile delivery in a modern enterprise E：the primary and highest authority responsible for the oversight and support of data governance activities 正确答案：E 你的答案：E 解析：3.1.3
        • 2. Data Governance Council (DGC) 数据治理委员会
          • Manages data governance initiatives (e.g., development of policies or metrics), issues, and escalations. Consists of executive according to the operating model used.
          • 51. Which one of the following is typically Not part of the data Governance Council? A：Senior managers as executive data stewards B：Chief Information officer C：Chief Executive Officer D：Data Management Leader E：Data Architect 正确答案：E 你的答案：B 解析：3.1.3，E在IT里，属执法，非立法DGO
          • 57. According to the DAMA DMBOK the Data Governance Council (DGC) is the highest authority organization for data governance in an organization who should typically chair this Council? A：the chair should rotate across the Data Owners B：Any Executive/C-level participant in the DGC C：Chief Data Steward (Business)/Chief Data Officer D：The Chief Data architect E：The Chief information Officer (ClO) 正确答案：C 你的答案：C 解析：3.1.3
          • 58. What Organization Structure should set the overall direction for Data Governance A：Data Quality Board B：Data governance office C：IT Leadership Team D：PMO E：Data Governance Council 正确答案：E 你的答案：E 解析：B偏执行
        • 3. Data Governance Office (DGO) 数据治理办公室
          • Ongoing focus on enterprise-level data definitions and data management standards across all DAMA-DMBOK Knowledge Areas. Consists of coordinating roles that are labelled as data stewards 数据管理专员 or custodians 数据保管人, and data owners 数据拥有者.
          • 63. Data Governance touch points throughout the project lifecycle are facilitated by this organization A：The data Stewards office B：the master data office C：The project Management Office D：The Data Governance office E：The Data Governance Steering Committee 指导委员会 正确答案：D 你的答案：E 解析：：DE中D各个涉及触点和执行层面
        • 4. Data Stewardship Teams 数据管理团队
          • Communities of interest focused on one or more specific subject-areas or projects, collaborating or consulting with project teams on data definitions and data management standards related to the focus. Consists of business and technical data stewards and data analysts. 注重管理
        • 5. Local Data Governance Committee 本地数据治理委员会
          • Large organizations may have divisional or departmental data governance councils working under the auspices of an Enterprise DGC. Smaller organizations should try to avoid such complexity.
      • 1.4.3. Data Governance Operating Model Types 数据治理运营模型类型
        • 
        • Centralized 集中式
        • Replicated 分布式
        • Federated 联邦式
        • 70. The advantage of a decentralized data governance model over a centralized model is A：an increased level of ownership from local decision-making groups B：the cheaper execution of data governance operations. C：the common metadata repository configurations D：the easier implementation of industry data models E：having a common approach to resolving data governance issues 正确答案：B 你的答案：B 解析：3.1.3. 题解：基于现有封装更廉价。3.数据治理运营模型类型在集中式管理模式中，数据治理组织监督所有业务领域中的活动。在分布式管理模式中，每个业务单元中采用相同的数据治理运营模型和标准。在联邦式管理模式中，数据治理组织与多个业务单元协同，以维护一致的定义和标准。企业数据治理运营模型示例如图3-4所示（参见图3-4和第16章）。
      • 1.4.4. Data Stewardship 数据管理专员的职责
        • Data Stewardship is the most common label to describe accountability and responsibility for data and processes that ensure effective control and use of data assets.
        • The focus of stewardship activities will differ from organization to organization, depending on organizational strategy, culture, the problems an organization is trying to solve, its level of data management maturity, and the formality of its stewardship program.
          • Creating and managing core Metadata
            • 81. one of a business data stewards key responsibilities is to A：manage metadata B：manage the calendar of the business data owner C：manage business process implementation D：manage data storage and operations E：manage the availability of the business intelligence solution 正确答案：A 你的答案：E 解析：3.1.3 技术管理专员（Technical Data Stewards）.他们是某个知识额域内工作的IT专业人员，如般据集成专家、数据库管理员、商务智能专家、数螺质量分析师或元数据管理员，
          • Documenting rules and standards
            • 28. who writes the data governance policy? A：Data governance council members B：Data steward, working groups or project teams, etc. C：Chief or head of data governance council D：Head of Data or information architecture E：all 正确答案：B 你的答案：A 解析：正确答案：B相关章节：3.1.3 数据治理题解：Policy已经较为具体，其他选项级别过高把握更抽象的战略5.数据管理岗位的类型管理专员（Steward，直译为管家，本书译为管理专员）指其职责是为别人管理财产的人。数据管理专员代表他人的利益并为组织的最佳利益来管理数据资产（McGilvray，2008）。数据管理专员代表所有相关方的利益，必须从企业的角度来确保企业数据的高质量和有效使用。有效的数据管理专员对数据治理活动负责，并有部分时间专门从事这些活动。根据组织的复杂性和数据治理规划的目标，各个组织中正式任命的这些数据管理专员在其工作职位上会有一些区别.
          • Managing data quality issues
            • 65. Data Stewards are most likely to be responsible for: A：Content and Document Management B：Data Storage and Operations C：Data lntegration and lnteroperability D：Data Governance and Data Quality E：Data Modelling and Data Security 正确答案：D 你的答案：D 解析：3.1.3
          • Executing operational data governance activities
        • 50. Ideally data stewards should be organized by A：data function B：department C：data domain 数据域 D：division E：none 正确答案：C 你的答案：C 解析：题解：4）业务数据管理专员（Business Data Stewards）。他们是业务领域专业人士，通常是公认的领域专家，对一个数据域负责。他们和利益相关方共同定义和控制数据。
        • 61. What are the primary responsibilities of a data steward? A：Analyzing data quality B：A business role appointed to take responsibility for the quality and use of their organization's data assets C：The manager responsible for writing policies and standards that define the data management program for an organization D：Identifying data problems issues E：The data analyst who is the subject matter expert (SME) on a set of reference data 正确答案：B 你的答案：B 解析：3.1.3
      • 1.4.5. Types of Data Steward 数据管理岗位的类型
        • Data Stewards manage data assets on behalf of others and in the best interests of the organization (McGilvray, 2008)
          • 67. The primary role of a data steward is A：to perform program code reviews B：to encourage certification in data management best practices across the organization C：to manage data assets on behalf of others and in the best interests of the organization D：to interfere in lT projects. E：to manage the data quality business unit. 正确答案：C 你的答案：C 解析：3.1.3
        • Types
          • 1. Chief Data Stewards 首席数据管理专员
          • 2. Executive Data Stewards 高级数据管理专员
          • 3. Enterprise Data Stewards 企业数据管理专员
          • 4. Business Data Stewards 业务数据管理专员
          • 5. A Data Owner 数据所有者
          • 6. Technical Data Stewards 技术数据管理专员
          • 7. Coordinating Data Stewards 协调数据管理专员
        • “the best Data Stewards are often found, not made” (DAMA, 2009)
        • 55. who is most responsible for communicating and promoting awareness on the value of Data Governance in the organization? A：Data Champions B：The data governance office C：Everyone in the Data Management Community 管理社区 D：Data Owners stewards E：The data governance council 正确答案：C 你的答案：E 解析：E是高层只覆盖一小面
      • 1.4.6. Data Policies 数据制度
        • Data policies are directives that codify principles and management intent into fundamental rules governing the creation, acquisition, integrity, security, quality, and use of data and information.
        • Data policies are global. They support data standards, as well as expected behaviors related to key aspects of data management and use. Data policies vary widely across organizations.
        • Policy vs Standards
          • Data policies describe the ‘what’ of data governances (what to do and what not to do), while standards and procedures describe ‘how’ to do data governance.
          • There should be relatively few data policies, and they should be stated briefly and directly.
      • 1.4.7. Data Asset Valuation 数据资产估值
        • 1. Replacement cost 替换成本
          • The replacement or recovery cost of data lost in a disaster or data breach, including thetransactions, domains, catalogs, documents and metrics within an organization
        • 2. Market value 市场价值
          • The value as a business asset at the time of a merger or acquisition
        • 3. Identified opportunities 发现商机
          • The value of income that can be gained from opportunities identified in the data(in Business Intelligence), by using the data for transactions, or by selling the data.
        • 4. Selling data 售卖数据
          • Some organizations package data as a product or sell insights gained from their data.
        • 5. Risk cost 风险成本
          • A valuation based on potential penalties, remediation costs, and litigation expenses, derivedfrom legal or regulatory risk from:
            • The absence of data that is required to be present.
            • The presence of data that should not be present
            • Data that is incorrect, causing damage to customers, company finances, and reputation in addition to the above costs.
            • Reduction in risk and risk cost is offset by the operational intervention costs to improve and certify data
        • 6. 26. Data asset valuation can be established by all of the following methods EXCEPT A：by estimation B：by performing an inventory. 通过执行清单 C：at the time of corporation sale D：as a replacement cost E：as a replacement cost 正确答案：B 你的答案：C 解析：3.1.3：B执行清单无法反应资产和定价 数据生命周期的大多数阶段涉及成本（包括获取数据、存储、管理和处置）。数据只有在使用时才有价值，使用时数据还产生了与风险管理相关的成本.因此，当使用数据的经济效益超过了上述成本时，就会显现其价值。其他度量价值的方式包括：1）替换成本（Replacement Cost），在灾难性数据破坏事件或者数据中断时，数据替换或恢复的成本，包括组织内的交易、域、目录、文档和指标信息等。2）市场价值（Market Value），兼并或收购企业时作为企业资产的价值。3）发现商机（Identified Opportunities）。通过交易数据或者通过售卖数据，从数据（商务智能）中发现商机获得的收入价值。4）售卖数据（Selling Data），一些组织为产品或销售将数据打包从数据中获得的洞察。5）风险成本（Risk Cost）。
        • 7. 69. which of the following is NOT an approach to data valuation? A：Cost of obtaining and storing data B：Cost of replacing data if it were lost C：what the data could be sold for D：Enterprise data modelling E：Expected revenue from innovative uses of data 正确答案：D 你的答案：D 解析：3.1.3：数据生命周期的大多数阶段涉及成本（包括获取数据、存储、管理和处置）。数据只有在使用时才有价值，使用时数据还产生了与风险管理相关的成本。因此，当使用数据的经济效益超过了上述成本时，就会显现其价值，其他度量价值的方式包括：1）替换成本（Replacement Cost）.在灾难性数据破坏事件或者数据中断时，数据替换或恢复的成本，包括组织内的交易、域、目录、文档和指标信息等。2）市场价值（Market Value）.兼并或收购企业时作为企业资产的价值。3）发现商机（Identified Opportunities），通过交易数据或者通过售卖数据，从数据（商务智能）中发现商机获得的收入价值。4）售卖数据（Selling Data）。一些组织为产品或销售将数据打包从数据中获得的洞察，5）风险成本（Risk Cost）.它是基于潜在罚款、补救成本和诉讼费用的估价。
        • 8. Principles for Data Asset Accounting
          • 1. To describe the concept of information asset value, one can translate Generally Accepted Accounting Principles 公认会计准则 into Generally Accepted Information Principles
            • Accountability Principle 问责原则
            • Asset Principle 资产原则
            • Audit Principle 审计原则
            • Due Diligence Principle 尽调原则
            • Going Concern Principle 持续经营原则
            • Level of Valuation Principle 估值级别原则
            • Liability Principle 担责原则
            • Quality Principle 质量原则
            • Risk Principle 风险原则
            • Value Principle 价值原则
  • 2. Activities
    • 2.1. Define Data Governance for the Organization 规划数据治理
      • 2.1.1. Data governance activities cross organizational and system boundaries in support of an integrated view of data. Data governance is most effective when it is an enterprise effort, rather than isolated to a particular functional area.
      • 2.1.2. Perform Readiness Assessment 执行就绪评估
        • 1. Data management maturity 数据管理成熟度
          • Understand what the organization does with data; measure its current datamanagement capabilities and capacity
        • 2. Capacity to change 变革能力
          • Since DG requires behavioral change, it is important to measure the capacity for theorganization to change behaviors required for adapting DG
        • 3. Collaborative readiness 协作准备
          • This assessment characterizes the organization’s ability to collaborate in the management and use of data.
        • 4. Business alignment 与业务保持一致
          • a business alignment assessmentexamines how well the organization aligns uses of data with business strategy.
      • 2.1.3. Perform Discovery and Business Alignment 探索与业务一致
        • A DG program must contribute to the organization by identifying and delivering on specific benefits
        • Discovery activity will identify and assess the effectiveness of existing policies and guidelines – what risks they address, what behaviors they encourage, and how well they have been implemented.
        • Data Quality (DQ) analysis is part of discovery
        • Business alignment attaches business benefits to DG program elements.
        • Assessment of data management practices is another key aspect of the data governance discovery process.
        • Derive a list of DG requirements from the discovery and alignment activities.
      • 2.1.4. Develop Organizational Touch Points 制定组织触点
        • 
        • The touch points that the CDO influences support the organization’s cohesiveness 凝聚力 in managing its data, therefore, increasing its nimbleness to use its data. In essence, this is a vision of how DG will be perceived by the organization.
          • Procurement and Contracts
          • Budget and Funding
          • Regulatory Compliance 法规遵从性
          • SDLC / development framework 开发框架
    • 2.2. Develop Data Governance Strategy 制定数据治理战略
      • 2.2.1. A data governance strategy defines the scope and approach to governance efforts. DG strategy should be defined comprehensively and articulated in relation to the overall business strategy, as well as to data management and IT strategies.
        • 1. Charter: 章程
          • Identifies the business drivers, vision, mission, and principles for data governance, including readiness assessment, internal process discovery, and current issues or success criteria
        • 2. Operating framework and accountabilities: 运营框架和职责
          • Defines structure and responsibility for data governance activities
          • 54. In the Information Management Lifecycle，the data Governance Activity Define the Data Governance framework's considered in which lifecycle stage? A：Maintain Use B：Create & Acquire C：Enable D：specify E：Plan 正确答案：E 你的答案：E 解析： 3.2.1规划组织的数据治理 数据治理工作必须支持业务战略和目标。一个组织的业务战略和目标影响着组织的数据战略，以及数据治理和数据管理在组织的运营方式。
        • 3. Implementation roadmap: 实施路线图
          • Timeframes for the roll out of policies and directives, business glossary,architecture, asset valuation, standards and procedures, expected changes to business and technologyprocesses, and deliverables to support auditing activities and regulatory compliance
        • 4. Plan for operational success: 为成功运营制定计划
          • Describing a target state of sustainable data governance activities
      • 2.2.2. Define the DG Operating Framework
        • Consider
          • Value of data to the organization
            • If an organization sells data, obviously DG has a huge businessimpact.
          • Business model
            • Decentralized business vs. centralized, local vs. international, etc. are factors thatinfluence how business occurs, and therefore, how the DG operating model is defined.
          • Cultural factors
            • Such as acceptance of discipline and adaptability to change. Some organizations willresist the imposition of governance by policy and principle.
          • Impact of regulation 监管影响
            • Highly regulated organizations will have a different mindset and operating modelof DG than those less regulated.
          • 66. what area do you not consider when developing a 'data governance operating model? A：The value of data to the organization B：Impact of regulation C：the business model-decentralized versus centralized D：The availability of industry data models E：Cultural factors-such as acceptance of discipline and adaptability to change. 正确答案：D 你的答案：D 解析：3.2.2：1.定义数螺治理通营柜架开发胶螺治理的基本定义很容易，但是创建一个组织采用的通营板架可熊很图难。在构建组织的运营概架时据要考虑以下几个方面：1）数据对组织的价值。如果一个组织出售数据，显然数据治理具有巨大的业务影响力.将数据作为最有价值事物的组织（如Facebook、亚马避）将需要一个反院数据角色的通营模式，对于数据是操作润清剂的组织，数据治理形式就不那么严肃了。2）业务模式。分散式与集中式、本她化与国际化等是影响业务发生方式以及如何定义数据治理运营模式的因素。与特定IT策路、数据架构和应用程序集成功能的链接，应反缺在目标运营板架设计中（圈3-6）。3）文化因素。就像个人接受行为准则、适应变化的过程一样，一些组织也金抵制制度和原则的实施，开展治理战略需要提倡一种与组织文化相适应的运营模式，同时持续地进行变革。4）监管影响，与受监管程度较低的组织相比，受监管程度较高的组织具有不同的数据治理心态和运营模式，可能还与风险管理或法律团队有联
        • An Example of an Operating Framework
          • 
          • This kind of artifact must be customized to meet the needs of a specific organization.
          • Layers of data governance are often part of the solution. This means determining where accountability should reside for stewardship activities, who owns the data, etc.
          • The operating model also defines the interaction between the governance organization and the people responsible for data management projects or initiatives, the engagement of change management activities to introduce this new program, and the model for issue management resolution pathways through governance.
      • 2.2.3. Develop Goals, Principles, and Policies
        • Policies examples
          • The Data Governance Office (DGO) will certify 确认 data for use by the organization.
          • Business owners will be approved by the Data Governance Office.
          • Business owners will designate Data Stewards from their business capability areas. The Data Stewards will have day-to-day 日常 responsibility for coordinating data governance activities.
          • Whenever possible 尽可能的, standardized reporting and/or dashboards/scorecards will be made available to serve the majority of business needs.
          • Certified Users will be granted access to Certified Data for ad hoc 专门的针对的 /non-standard reporting.
          • All certified data will be evaluated on a regular basis to assess its accuracy, completeness 完整性, consistency 一致性, accessibility, uniqueness, compliance, and efficiency.
      • 2.2.4. Underwrite 推动 Data Management Projects
        • The key to promoting them is to articulate the ways they improve efficiency and reduce risk.
        • The DGC may also coordinate data management improvement efforts with large programs with enterprise-wide scope.
        • Every project with a significant data component (and almost every project has these) should capture data management requirements early in the SDLC (planning and design phases).
      • 2.2.5. Engage Change Management 参与变革管理
        • For many organizations, the formality and discipline inherent in DG differ from existing practices. Adopting them requires that people change their behaviors and interactions.
        • A formal Organizational Change Management (OCM) 组织变革管理 program, with the right executive sponsor, is critical to driving the behavioral changes required to sustain DG. Organizations should create a team responsible for:
          • 1. Planning 规划
          • 2. Training
          • 3. Influencing systems development 影响系统开发
          • 4. Policy implementation 制度实施
          • 5. Communications
            • Promoting the value of data assets:
            • Monitoring and acting on feedback about data governance activities
            • Implementing data management training
            • Measuring the effects of change management on in five key areas
              • Awareness of the need to change 意识到
              • Desire to participate and support the change 希望
              • Knowledge about how to change 知道
              • Ability to implement new skills and behaviors 具备
              • Reinforcement to keep the change in place 保持
            • Implementing new metrics and KPIs
      • 2.2.6. Engage in Issue Management
        • Including:
          • 1. Authority 授权
            • Questions regarding decision rights and procedures
          • 2. Change management escalations 变更管理升级
            • Issues arising from the change management process
          • 3. Compliance
            • Issues with meeting compliance requirements
          • 4. Conflicts:
            • Conflicting policies, procedures, business rules, names, definitions, standards, architecture, dataownerships and conflicting stakeholder interests in data and information
          • 5. Conformance 一致性
            • Issue related to conformance to policies, standards, architecture, and procedures
          • 6. Contracts 合同
            • Negotiation and review of data sharing agreements, buying and selling data, and cloud storage
          • 7. Data security and identity 身份识别
            • Privacy and confidentiality issues, including breach investigations
          • 8. Data quality
            • Detection and resolution of data quality issues, including disasters or security breaches
        • Data issue management is very important. It builds credibility 信任 for the DG team, has direct, positive effects on data consumers, and relieves the burden on production support teams. Solving issues also proves that data can be managed and its quality improved. Successful issue management requires control mechanisms that demonstrate the work effort and impact of resolution.
          • 1. Identifying, capturing, logging, tracking, and updating issues
          • 2. Assignment and tracking of action items
          • 3. Documenting stakeholder viewpoints and resolution alternatives
            • 15. In those organizations that specify 指定 data ownership roles，those individuals within their data governance mandate 数据治理期 A：moderate 缓和 data issues and conflicts B：define and guide data issues and conflicts C：define and lead data management maturity D：define data management priorities E：all 正确答案：D 你的答案：D 解析：3.2.2. 5.参与问题管理：问题管理是识别、量化、划分优先级和解决与数据治理相关的问题的过程
            • 80. As customers of data governance, the stakeholders may have different（）and（）due to legal regulatory financial 法律监管财务, operational or competitive demands. A：contract; litigation issues 诉讼问题 B：individual; collective needs C：drivers; levels of focus 焦点水平 D：levels of influence drivers E：none 正确答案：C 你的答案：D 解析：：利益相关者有相应的驱动力
          • 4. Determining, documenting, and communicating issue resolutions
          • 5. Facilitating objective, neutral discussions where all viewpoints are heard
            • 75. The two most important characteristics to facilitate data Governance within an organization are and A：acknowledgement credentials B：expertise，reward C：knowledge，respect D：trust，communication E：Expertise，respect 正确答案：D 你的答案：E 解析：3.2.2. 题解：很多问题可以在数据管理团队中被解决。需要沟通或者上报的问题必须被记录下来，并将其上报给数据管理团队或者更高级别的数据治理委员会。数据问题管理非常重要。通过问题管理为数据治理团队建立了信任，减轻了生产支持团队的负担，这对数据消费者有直接、积极的影响。通过解决问题也证明了数据管理和质量的提高。对于成功的问题管理需要有展示工作过程和消除影响的控制机制。
          • 6. Escalating issues to higher levels of authority
            • 
            • 59. what is the role of the data governance Council in defining an information security policy? A：The data Governance Council should define the data Security Policy B：The Data Governance Council should draft early versions of the data Security policy C：The data Governance Council should have no role in data Security D：The Data Governance Council should implement the Data Security Policy E：The Data Governance Council should review and approve the high-level Data Security 正确答案：E 你的答案：E 解析：3.1.3
      • 2.2.7. Assess Regulatory Compliance Requirements
        • Example
          • Accounting Standards
          • BCBS 239 and Basel II
          • CPG 235
            • 9. Data risk management includes A：declared systems of record; known data origins and uses B：root cause analysis C：standard naming and consistent use of data D：data to business alignment E：all 正确答案：B 你的答案：B 解析：3.2.2）CPG235。澳大利亚审慎监管局（APRA）负责监督银行和保险实体，公布了一些标准和指南以帮助被监管对象满足这些标准，其中包括CPG235，一个管理数据风险的标准。制定这个标准的目的是解决数据风险的来源，并在整个生命周期中管理数据。
          • PCI-DSS
          • Solvency II
          • Privacy laws
        • Data governance organizations work with other business and technical leadership to evaluate the implications of regulations. The organization must determine, for example,
          • 1. In what ways is a regulation relevant to the organization?
          • 2. What constitutes compliance? What policies and procedures will be required to achieve compliance?
          • 3. When is compliance required? How and when is compliance monitored?
          • 4. Can the organization adopt industry standards to achieve compliance?
          • 5. How is compliance demonstrated?
          • 6. What is the risk of and penalty for non-compliance?
          • 7. How is non-compliance identified and reported? How is non-compliance managed and rectified?
    • 2.3. Implement Data Governance
      • 2.3.1. Data governance cannot be implemented overnight. It requires planning – not only to account for organizational change, but also simply because it includes many complex activities that need to be coordinated. It is best to create an implementation roadmap that illustrates the timeframes for and relationship between different activities.
      • 2.3.2. Sponsor Data Standards and Procedures
        • 1. Data standards can take different forms depending on what they describe:
        • 2. They are usually drafted by data management professionals.
        • 3. Data standards should be reviewed, approved and adopted by the DGC, or a delegated workgroup, such as a Data Standards Steering Committee.
        • 4. Data standards must be effectively communicated, monitored, and periodically reviewed and updated.
        • 5. Most importantly, there must be a means to enforce them. Data can be measured against standards.
        • 6. Examples of concepts that can be standardized within the Data Management Knowledge Areas include:
          • 1. Data Architecture: Enterprise data models, tool standards, and system naming conventions
          • 2. Data Modeling and Design: Data model management procedures, data modeling naming conventions,definition standards, standard domains, and standard abbreviations
          • 3. Data Storage and Operations: Tool standards, standards for database recovery and business continuity,database performance, data retention, and external data acquisition
          • 4. Data Security: Data access security standards, monitoring and audit procedures, storage securitystandards, and training requirements
          • 5. Data Integration: Standard methods and tools used for data integration and interoperability
          • 6. Documents and Content: Content management standards and procedures, including use of enterprisetaxonomies, support for legal discovery, document and email retention periods, electronic signatures, andreport distribution approaches
          • 7. Reference and Master Data: Reference Data Management control procedures, systems of data record,assertions establishing and mandating use, standards for entity resolution
          • 8. Data Warehousing and Business Intelligence: Tool standard, processing standards and procedures,report and visualization formatting standards, standards for Big Data handling
          • 9. Metadata: Standard business and technical Metadata to be captured, Metadata integration procedures andusage
          • 10. Data Quality: Data quality rules, standard measurement methodologies, data remediation standards andprocedures
          • 11. Big Data and Data Science: Data source identification, authority, acquisition, system of record, sharingand refresh
      • 2.3.3. Develop a Business Glossary
        • Data Stewards are generally responsible for business glossary content
          • 1. Enable common understanding of the core business concepts and terminology
          • 2. Reduce the risk that data will be misused due to inconsistent understanding of the business concepts
            • 71. The failure to gain acceptance of a business glossary may be due to ineffective A：Metadata Management B：Content and Document Management C：Business architecture D：Data security E：Data Governance 正确答案：E 你的答案：C 解析：3.2.2. 题解：2.制定业务术语表数据管理专员通常负责整理业务术语表的内容。由于人们说话用词习惯不同，所以建立术语表是必要的。由于数据代表的是自身之外的事务，因此数据的明确定义尤为重要（Chisholm，2010）。
          • 3. Improve the alignment between technology assets (with their technical naming conventions) and the business organization
          • 4. Maximize search capability and enable access to documented institutional knowledge
        • A business glossary is not merely a list of terms and definitions. Each term will also be associated with other valuable Metadata: synonyms, metrics, lineage, business rules, the steward responsible for the term, etc.
      • 2.3.4. Coordinate with Architecture Groups
        • The DGC sponsors and approves data architecture artifacts, such as a business-oriented enterprise data model
        • The enterprise data model should be reviewed, approved, and formally adopted by the DGC. This model must align with key business strategies, processes, organizations, and systems.
        • Data strategy and Data Architecture are central to coordination between the ‘Doing things right’ and ‘Doing the right things’ when managing data assets.
      • 2.3.5. Sponsor Data Asset Valuation 发起数据资产估值
        • Data and information are assets because they have or can create value
        • Value estimates can be built into a data strategy roadmap that will justify business cases for root cause solutions to quality issues, as well as for other governance initiatives.
        • Today’s accounting practices consider data an intangible asset, much like software, documentation, expert knowledge, trade secrets, and other intellectual property. That said, organizations find it challenging to put monetary value on data.
        • Some organizations start by estimating the value of business losses due to inadequate information. Information gaps –the difference between what information is needed and what is available – represent business liabilities. The costof closing or preventing gaps can be used to estimate of business value of the missing data.
          • 32. Information gaps-the difference between what information is needed and whatever trustworthy information is current available-represent A：lost revenues B：inadequate 不足 information C：business assets D：business liabilities E：business liabilities 正确答案：B 你的答案：B 解析：3.2.3有些组织首先应该估计由于信息不足而造成业务损失的价值。信息缺口——所需信息和可用信息之间的差异——代表业务负债。弥补或防止差距的成本可用于估算数据丢失的业务价值。参考这个思路，组织可以开发模型来评估实际存在信息的价值。
        • 12. which one of the activities below is a typical outcome of the Data Architecture Management function within data governance? A：Enforce data integrity as close to the data as possible and immediately detect and report violations of data integrity constraints B：ldentification of a "golden" record of the truth C：Maintain a central repository providing guidance for use of terms and rules D：Information value-chain analysis E：none 正确答案：D 你的答案：A 解析：A数据建模和设计B主数据管理C参考数据管理
    • 2.4. Embed Data Governance 嵌入数据治理
      • 2.4.1. One goal of the data governance organization is to embed in a range of processes behaviors related to managing data as an asset. The ongoing operation of DG requires planning. The operations plan contains the list of events required to implement and operate DG activities. It outlines activities, timing, and techniques necessary to sustain success.
  • 3. Tools and Techniques
    • 3.1. Data governance is fundamentally about organizational behavior. This is not a problem that can be solved through technology. However, there are tools that support the overall process.
    • 3.2. Before choosing a tool for a specific function, like a business glossary solution, an organization should define its overall governance goals and requirements with an eye to building out a tool set.
    • 3.3. Online Presence / Websites
      • 3.3.1. The Data Governance strategy and program charter, including vision, benefits, goals, principles, and implementation roadmap
      • 3.3.2. Data policies and data standards
      • 3.3.3. Descriptions of data stewardship roles and responsibilities
      • 3.3.4. Program news announcements
      • 3.3.5. Links to forums for a Data Governance Community of Interest
      • 3.3.6. Links to executive messages regarding data governance topics
      • 3.3.7. Reports on Data Quality measurements
      • 3.3.8. Procedures for issue identification and escalation
      • 3.3.9. Links to request services or capture issues
      • 3.3.10. Documents, presentations, and training programs with links to related online resources
      • 3.3.11. Data Governance program contact information
    • 3.4. Business Glossary 业务术语表
      • 3.4.1. A Business Glossary is a core DG tool. It houses agreed-upon definitions of business terms and relates these to data. There are many business glossary tools available, some as part of larger ERP systems, data integration tools, or Metadata management tools, and some as standalone tools
    • 3.5. Workflow Tools 工作流工具
      • 3.5.1. Larger organizations may want to consider a robust workflow tool to manage processes, such as the implementation of new data governance policies. These tools connect processes to documents, and can be useful in policy administration and issue resolution.
    • 3.6. Document Management Tools 文档管理工具
      • 3.6.1. Very often, a document management tool is used by governance teams to assist in managing policies and procedures.
    • 3.7. Data Governance Scorecards 数据治理计分卡
      • 3.7.1. The collection of metrics to track data governance activities and compliance with policies can be reported up to the Data Governance Council and Data Governance Steering Committees on an automated scorecard.
      • 3.7.2. 43. when developing a data governance scorecard A：develop measures that roll up B：develop high level measures only : it is a strategic initiative C：link every metric to a dimension quality D：assign ownership of the measure structure E：None 正确答案：A 你的答案：A 解析：题解：3.3.5数据治理记分卡它是跟踪数据治理活动和制度遵从性的指标集合，通过自动记分卡的形式向数据治理委员会和数据治理指导委员会报告。
  • 4. Implementation Guidelines
    • 4.1. Most rollout strategies are incremental, either applying DG first to a large effort, such as MDM, or by a region or division. Rarely is DG deployed enterprise-wide as a first effort.
      • 4.1.1. 68. Adoption of a Data Governance program is most likely to succeed A：when the CDO is a charismatic leader B：in 1 or 2 months with a large consulting team C：with an incremental rollout strategy. D：when dictated 听写by senior executives. E：when the entire enterprise is partaking 参与 at once 正确答案：C 你的答案：E 解析：正确答案：C来源：3.2.2题解：增量扩展更容易成功。数据治理委员会还可以与企业范围内的大型项目集配合开展数据管理改进工作。主数据管理项目，如企业资源计划（ERP）、客户关系管理（CRM）和全球零件清单等都是很好的选择。
    • 4.2. Organization and Culture
      • 4.2.1. Effective and long-lasting data governance programs require a cultural shift in organizational thinking and behavior about data, as well as an ongoing program of change management to support the new thinking, behaviors, policies, and processes to achieve the desired future state of behavior around data.
        • 7. Successful data Governance programs are A：bottom-up collaborations amongst business stakeholders B：dependent on fit with culture and capabilities of the organization C：a blend of bottom-up collaborations and top-down implementations D：top-down implementations with executive leadership E：all 正确答案：B 你的答案：C 解析：正确答案：B来源：3.4.1题解：有效而持久的数据治理需要组织文化的转变和持续的变革管理，文化包括组织思维和数据行为，变革包括为实现未来预期的行为状态而支持的新思维、行为、策略和流程。无论数据治理战略多么精确、多么独特，忽视企业文化因素都会减少成功的概率。实施战略必须专注于变革管理。
    • 4.3. Adjustment and Communication
      • 4.3.1. Data Governance programs are implemented incrementally within the context of a wider business and data management strategy. Success requires keeping the wider goals in mind while putting the pieces in place. The DG team will need to be flexible and adjust its approach as conditions shift. Tools required to manage and communicate changes include:
        • Business / DG strategy map 业务战略/数据治理战略蓝图
          • This map connects DG activity with business needs. Periodically measuringand communicating how DG is helping the business is vital to obtain ongoing support for the program.
        • DG roadmap 数据治理路线图
          • 27. A data governance roadmap should include all of the following EXCEPT A：technologies and communications. B：tasks and data index inventory 数据索引清单 C：policies and processes D：people and organizational structures E：all 正确答案：B 你的答案：D 解析：roadmap是路线更加宏观，data index inventory（数据索引清单）太具体
          • The roadmap to DG should not be rigid. It should be adapted to changes in businessenvironment or priorities.
        • Ongoing business case for DG 数据治理的持续业务案例
          • The business case must be adjusted periodically to reflect changingpriorities and financial realities of the organization.
        • DG metrics 数据治理指标
          • Metrics will need to grow and change as the DG program matures.
  • 5. Metrics
    • 5.1. Value
      • 5.1.1. Contributions to business objectives
      • 5.1.2. Reduction of risk
      • 5.1.3. Improved efficiency in operations
    • 5.2. Effectiveness 有效性
      • 5.2.1. Achievement of goals and objectives
      • 5.2.2. Extent stewards are using the relevant tools
      • 5.2.3. Effectiveness of communication
      • 5.2.4. Effectiveness of education/training
      • 5.2.5. Speed of change adoption 采纳变革的速度
    • 5.3. Sustainability
      • 5.3.1. Performance of policies and processes (i.e., are they working appropriately?)
      • 5.3.2. Conformance 遵从 to standards and procedures (i.e., are staff following the guidance and changing behavior as necessary?)
  • 6. Works Cited / Recommended
    • 6.1. 5. The role of the enterprise data model in data governance is all of the following EXCEPT to A：understand entity and attribute definitions. B：act as a template for projects allowing a rapid progression through design stages C：understand the business definitions of data D：understand how the application manages historical data. E：all 正确答案：D 你的答案：D 解析： D属于归档与日志管理与策略，与企业数据模型无关
    • 6.2. 6. Aspects of data governance include A：a data stewards data custodians and data owners B：lifecycle. Develop Execute Sustain. Evolve (DESE) and information. C：data quality, standardization consolidation and regulatory compliance D：people，process and business goals. E：data quality, data security，metadata 正确答案：D 你的答案：C 解析：语境关系图
    • 6.3. 11. The governance team plays a pivotal 关键 role in ensuring the ( ) are selected A：defined roles B：policies and procedures C：ROl figures D：right projects E：all 正确答案：D 你的答案：B 解析：其他选项范围过小
    • 6.4. 18. Data governance should ensure that when implementing a cloud solution，the SAL (Security Aspect Letter) must include for vendor delegated tasks A：due diligence for data protection 数据保护尽调 B：fit for use tests in data development C：appropriate testing requirements. D：data defect correction processes E：all 正确答案：A 你的答案：A 解析：题解：Security Aspects Letter.（SAL）means a document issued by a contracting authority（定约当局）which forms an integral part of a Classified Contract identifying the security requirements，or each element of that Classified Contract requiring security protection.
    • 6.5. 19. The data governance inventory 数据治理清单 particularly useful in a data governance program is from A：meta-data technologies B：application list. C：data volumetrics tools 数据体积工具 D：social media tools E：none 正确答案：A 你的答案：C 解析：其他不相关
    • 6.6. 20. Data governance stakeholders include all of the following EXCEPT A：product consumers B：regulatory compliance officers C：financial management. D：those operational interests that drive efficiency and effectiveness E：all 正确答案：A 你的答案：D 解析：A产品的无关
    • 6.7. 21. Data Governance success factors include all of the following EXCEPT A：political will. B：motivation C：autonomy 自治 D：commitment. E：compliance 正确答案：C 你的答案：C 解析：C与需要治理的思路相反
    • 6.8. 22. Data governance may leverage all of the following for data classification and retention 保留 EXCEPT from A：records management systems B：database retention policy 数据库保留政策 C：application service level agreements. D：third party data usage and handling specifications E：all 正确答案：C 你的答案：C 解析：C是应用层面的服务等级协议（app延迟，稳定性等），不是同一层的约束
    • 6.9. 23. One place data governance has evolved from is the_( )_developed for cross-organizational data warehouse projects for technical as well as business disputes 纠纷 A：Bl Arbitration Board 仲裁委员会 B：Data governance council C：Change Management Committee D：MDM Steering Committee 主数据管理指导委员会 E：Data Governance Steering Council 正确答案：A 你的答案：B 解析：仲裁处理纠纷
    • 6.10. 24. Assigning data stewards is a result of all of the following EXCEPT the A：size of your enterprise B：organizational maturity of your data governance program C：location of your controlling group and value of data assets D：scope of governed data E：all 正确答案：A 你的答案：A 解析：3.1.3：A没有说出此职位的作用和解决的问题，单纯从人数出发
    • 6.11. 25. when starting a Data Governance program, the biggest challenge is to A：determine the scope of data to be managed B：defining a single data subject such as CUSTOMER. C：monitor the KPls D：reducing redundant data in an organization E：none 正确答案：A 你的答案：A 解析：：3.2.2制定数据治理战略数据治理战略定义了治理工作的范围和方法。
    • 6.12. 29. Data governance includes all EXCEPT A：exercise of authority 行权 B：monitoring of the management of data assets. C：high-level planning D：data operations E：Define the DG Operating Framework 正确答案：D 你的答案：D 解析：数据操作属于数据库的基本功能
    • 6.13. 30. Reasons to govern data architecture include all of the following EXCEPT A：you require a matrix map of business unit interactions with data entities B：you need to know where data is reported all the time C：the core data management processes of IT departments touch only a small percentage of the enterprise data resource D：you need a subject model that describes the various data domains E：all 正确答案：B 你的答案：C 解析：：B是数据报告的位置，与题干治理数据架构无关
    • 6.14. 34. Data governance activities include all of the following EXCEPT A：make decisions about the application portfolio B：review and approve data architecture C：develop and approve data policies, standards and procedures D：monitor application design to ensure regulatory compliance E：Develop Data Governance Strategy 正确答案：A 你的答案：A 解析：A是应用，IT管，不是数据的
    • 6.15. 37. () governance consists of 由..组成 addressing a current critical issue A：Protective B：Pre-emptive 抢占式 C：Reactive 反应式 D：Performance 性能 E：central 中央 正确答案：C 你的答案：C 解析：网络：Reactive governance means acting to address an issue or resolve a problem before it becomes a crisis.反应性治理意味着在问题变成危机之前采取行动解决问题或解决问题。
    • 6.16. 64. which of these is NOT a standard motivation for data governance A：Devolved governance 权力下放 B：Decentralized Governance 去中心化 C：Pre-emptive governance 先制 D：Proactive governance 主动 E：Reactive governance 反应性治理 正确答案：A 你的答案：E 解析：下放类似于转移和放弃
    • 6.17. 39. Data Governance roles include all of the following EXCEPT data A：custodian 保管人 B：scribe 抄写员 C：steward 管理专员 D：architect. E：owner 正确答案：B 你的答案：B 解析：B没出现过，更像脚本，A和E同义
    • 6.18. 40. which of the following high-pressured high-visibility items most often impact Data Governance? A：Data quality，security and compliance issues B：ability to track goals quantitatively C：Reducing complexity within the organization D：Standardization and consolidation E：all 正确答案：A 你的答案：B 解析：A在数据治理章节高频出现
    • 6.19. 47. All of the following are important aspects of data governance for MDM 主数据管理 EXCEPT A：ensuring data policies are observed B：managing data entities and critical data elements C：establishing accountability 问责for high-quality data maintenance D：database selection standards E：Evaluate and Assess data Sources 正确答案：B 你的答案：D 解析：B是数据管理的职责。数据治理（Data Governance，DG）的定义是在管理数据资产过程中行使权力和管控，包括计划、监控和实施。
    • 6.20. 49. Governance is the activity that includes all of the following EXCEPT A：establishing socio-political structures such as tribes and families. 建立部落和家庭的社会政治结构 B：defining decision rights and defining processes C：governing the things that a government does D：corporate governments that provide the power structure in a business entity E：Define Data Governance for the Organization 正确答案：A 你的答案：D 解析：数据治理与社会政治无关
    • 6.21. 52. Over a decade an organization has rationalized implementation of party concepts 党派概念 from 48 systems to 3.This is a result of good: A：data operations and system rationalization 合理化 B：data architecture and data governance C：data architecture and data warehousing D：system rationalization and metadata management E：data quality and data governance 正确答案：B 你的答案：B 解析：题解：data operations，data warehousing，metadata management，data quality. 这些均不能解决这个问题，只有B才可以
    • 6.22. 53. An annual enterprise data architecture report is comprised of a summary of enterprise data model updates, project compliance and variances and a measurement of: A：reference and master data compliance B：database backup compliance. C：data security compliance D：data warehouse compliance E：data landscape compliance 全景 正确答案：E 你的答案：E 解析：数据全景合规，其他只涉及一方面
    • 6.23. 74. The easiest place to implement a Data Governance program is often with A：bargaining for exceptions to data policy. B：demanding Roi justification for each governance policy and process C：new business process D：treating data issues as lT problems E：Staring a project 正确答案：C 你的答案：E 解析：新业务更容易实施，没有牵绊
    • 6.24. 76. Data technology alignment processes in a Data Governance (DG)program seek to do all of the following EXCEPT A：promote technology decisions and implementations that are compatible with data management practices B：identify requirements for and participate in selection of data management MDM and data quality tools and technologies C：ensure that DG practices and lT practices are synergistic，consistent and free of conflict D：develop a hierarchical organizational architecture for DG and lT operations E：all 正确答案：D 你的答案：D 解析：协调不涉及架构
    • 6.25. 77. Making the case for funding a data governance program can be done through A：achieving 'cheap or quick wins in correcting key data 便宜或快速赢得 B：groundswell of interest. 兴趣高涨 C：reacting to stock market value of the company. D：picking the important company project to influence. E：none 正确答案：A 你的答案：A 解析：从小处和容易完成见效的地方着眼与启动
    • 6.26. 78. Decision rights 决策权 in Data Governance A：specify access，retention and contribution to value B：provide absolute authority and unrestricted power. C：specify how management should control ongoing operations D：are a means by which to implement authority E：No answer 正确答案：E 你的答案：A 解析：B过于极端