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Data Governance Flashcards

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1
Q

The primary and highest authority organisation for data
governance. Includes senior managers serving as executive
data stewards, DM Leader and the CIO.

A

Data Governance Council

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2
Q

One or more cross-functional groups of people who coordinate data
who are responsible for support and oversight of a particular
data management initiative.

A

DATA STEWARDSHIP STEERING COMMITTEE

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3
Q

One or more business data stewards collaborating on an area
of data management, typically within an assigned subject area,
led by a Coordinating Data Steward.

A

DATA STEWARDSHIP TEAM

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4
Q

A strategic team responsible for measuring success and gathering metrics. A centralized organizational entity responsible for facilitating and coordinating Data Governance and/or Stewardship efforts for an organization.

A

Data Governance Office

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5
Q

Senior Managers who serve on a Data Governance
Council.

A

Executive Data Stewards

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6
Q

Leads and represents teams of business data stewards
in discussions across teams and with executive data
stewards. These data stewards are particularly
important in large organizations.

A

COORDINATING DATA STEWARD

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7
Q

A knowledge worker and business leader recognized as
a subject matter expert who is assigned accountability
for the data specifications and data quality of
specifically assigned business entities, subject areas or
databases.

A

BUSINESS DATA STEWARD

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8
Q

What is Data Governance

A

The exercise of authority and control (planning, monitoring, and enforcement) over the management of data assets.

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9
Q

What are the goals of Data Governance as stated in the DMBoK?

A
  1. Enable an organization to manage its data as an asset.
  2. Define, approve, communicate, and implement principles, policies, procedures, metrics, tools, and
    responsibilities for data management.
  3. Monitor and guide policy compliance, data usage, and management activities.
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10
Q

What is the purpose of Data Governance?

A

To ensure that data is managed properly, according to policies and best practices

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10
Q

What areas/subject are included in a DG program?

A

most programs include:
* Strategy
* Policy
* Standards and quality
* Oversight
* Compliance
* Issue management
* Data management projects
* Data asset valuation

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10
Q

Many organizations back into data governance via an
information management program driven by other business needs, such as ___________ by__________, or both.

A

Master Data Management (MDM), Major Data Problems

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10
Q

The most common driver for data governance is often ___________, especially for industries such as financial services and healthcare?

A

Regulatory Compliance

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11
Q

Drivers for data governance most often focus on ________ or _______.

A

Reducing Risks, Improving Processes

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12
Q

What are 3 ways of reducing risks in Data Governance?

A

o General risk management: Oversight of the risks data poses to finances or reputation, including response to legal (E-Discovery) and regulatory issues.

o Data security: Protection of data assets through controls for the availability, usability, integrity, consistency, auditability and security of data.

o Privacy: Control of private / confidential / Personal Identifying Information (PII) through policy and compliance monitoring.

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13
Q

What are 5 ways of improving processes in Data Governance?

A

o Regulatory compliance: The ability to respond efficiently and consistently to regulatory requirements.
o Data quality improvement: The ability to contribute to improved business performance by making data more reliable.
o Metadata Management: Establishment of a business glossary to define and locate data in the organization; ensuring the wide range of other Metadata is managed and made available to the
organization.
o Efficiency in development projects: SDLC improvements to address issues and opportunities in data management across the organization, including management of data-specific technical debt
through governance of the data lifecycle.
o Vendor management: Control of contracts dealing with data, such as cloud storage, external data purchase, sales of data as a product, and outsourcing data operations.

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14
Q

Data governance is not a one-time thing. Governing data requires an ongoing program focused on ensuring that an organization gets ________ from its data and reduces _______ related to data.

A

value, risks

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15
Q

True of False: Data governance is separate from IT governance.

A

True

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16
Q

What governance group makes decisions about IT investments, the IT application portfolio, and the IT project portfolio – in other words, hardware, software, and overall technical architecture?

A

IT Governance

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17
Q

DG provides what 6 things to manage data as an asset and to guide data management activities at all levels?

A

principles, policies, processes, framework, metrics, and oversight

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18
Q

What 6 principles can help set a strong foundation for data governance?

A
  • Leadership and strategy
  • Business-driven
  • Shared responsibility
  • Multi-layered
  • Framework-based
  • Principle-based
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19
Q

Data ______________ is focused on ensuring data is managed (the oversight of data) whereas Data ________________ is focused on managing data to achieve goals (the execution aspects of data).

A

Governance, Management

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20
Q

What are 4 principles for an organization to get more value from their data?

A
  • 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
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21
Q

In terms of political governance, what legislative-like functions does data governance serve?

A

defining policies, standards, and the Enterprise Data Architecture

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22
In terms of political governance, what judicial-like functions does data governance serve?
issue management and escalation
22
In terms of political governance, what executive-like functions does data governance serve?
protecting and serving, administrative responsibilities
23
Name the 5 organization structures involved with Data Governance
Data Governance Steering Committee Data Governance Council (DGC) Data Governance Office (DGO) Data Stewardship Teams Local Data Governance Committee
24
The primary and highest authority organization for data governance in an organization, responsible for oversight, support, and funding of data governance activities. What level of people are on it?
Data Governance Steering Committee Consists of a cross-functional group of senior executives.
25
This group manages data governance initiatives (e.g., development of policies or metrics), issues, and escalations. Who all works in this group?
Data Governance Council (DGC) Consists of executives according to the operating model used.
26
This group focuses on enterprise-level data definitions and data management standards across all DAMA-DMBOK Knowledge Areas. Who all works in this group?
Data Governance Office (DGO) Consists of coordinating roles that are labelled as data stewards or custodians, and data owners.
27
What is the name of the 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. Who all works in this group?
Data Stewardship Teams Consists of business and technical data stewards and data analysts.
28
Large organizations may have these divisional or departmental data governance councils working under the auspices of an Enterprise DGC. Who all works in this group?
Local Data Governance Committee or Working Groups
29
In a ___________ model, one Data Governance organization oversees all activities in all subject areas. In a _______________ model, the same DG operating model and standards are adopted by each business unit. In a ___________model, one Data Governance organization coordinates with multiple Business Units to maintain consistent definitions and standards.
centralized replicated federated
30
What is Data Stewardship?
The most common label to describe accountability and responsibility for data and processes that ensure effective control and use of data assets.
31
What are 4 activities that data stewards will focus on in most cases?
* Creating and managing core Metadata * Documenting rules and standards * Managing data quality issues * Executing operational data governance activities
32
________________ may chair data governance bodies in lieu of the CDO or may act as a CDO in a virtual (committee-based) or distributed data governance organization. They may also be Executive Sponsors.
Chief Data Stewards
33
____________ are senior managers who serve on a Data Governance Council.
Executive Data Stewards
34
__________ have oversight of a data domain across business functions.
Enterprise Data Stewards
35
____________ are business professionals, most often recognized subject matter experts, accountable for a subset of data. They work with stakeholders to define and control data.
Business Data Stewards
36
A ________ is a business Data Steward, who has approval authority for decisions about data within their domain.
Data Owner
37
_________ are IT professionals operating within one of the Knowledge Areas, such as Data Integration Specialists, Database Administrators, Business Intelligence Specialists, Data Quality Analysts or Metadata Administrators.
Technical Data Stewards
38
__________ lead and represent teams of business and technical Data Stewards in discussions across teams and with executive Data Stewards. Coordinating Data Stewards are particularly important in large organizations.
Coordinating Data Stewards
39
True of False: The best Data Stewards are made, not found
False
40
What are data policies?
Directives that codify principles and management intent into fundamental rules governing the creation, acquisition, integrity, security, quality, and use of data and information.
41
What is data asset valuation?
The process of understanding and calculating the economic value of data to an organization
42
What are 5 ways to measure data value?
* Replacement cost * Market value * Identified opportunities * Selling data * Risk cost
43
What are 4 Risks associated with Risk cost? Risk Cost is a valuation based on potential penalties, remediation costs, and litigation expenses, derived from legal or regulatory risk.
o The absence of data that is required to be present. o The presence of data that should not be present (e.g., unexpected data found during legal discovery; data that is required to be purged but has not been purged). o Data that is incorrect, causing damage to customers, company finances, and reputation in addition to the above costs. o Reduction in risk and risk cost is offset by the operational intervention costs to improve and certify data
44
Which data asset principle states that: An organization must identify individuals who are ultimately accountable for data and content of all types.
Accountability Principle
45
Which data asset principle states that: There is value in data and content, based on the ways these are used to meet an organization’s objectives, their intrinsic marketability, and/or their contribution to the organization’s goodwill (balance sheet) valuation. The value of information reflects its contribution to the organization offset by the cost of maintenance and movement.
Value Principle
46
Which data asset principle states that: Data and content of all types are assets and have characteristics of other assets. They should be managed, secured, and accounted for as other material or financial assets.
Asset Principle
47
Which data asset principle states that: The accuracy of data and content is subject to periodic audit by an independent body.
Audit Principle
48
Which data asset principle states that: If a risk is known, it must be reported. If a risk is possible, it must be confirmed. Data risks include risks related to poor data management practices.
Due Diligence Principle
49
Which data asset principle states that: Data and content are critical to successful, ongoing business operations and management
Going Concern Principle
50
Which data asset principle states that: Value the data as an asset at a level that makes the most sense, or is the easiest to measure.
Level of Valuation Principle
51
Which data asset principle states that: There is a financial liability connected to data or content based on regulatory and ethical misuse or mismanagement.
Liability Principle
52
Which data asset principle states that: The meaning, accuracy, and lifecycle of data and content can affect the financial status of the organization.
Quality Principle
53
Which data asset principle states that: There is risk associated with data and content. This risk must be formally recognized, either as a liability or through incurring costs to manage and reduce the inherent risk.
Risk Principle
54
What type of assessments describe the current state of an organization’s information management capabilities, maturity, and effectiveness?
Readiness Assessment
55
The aim of this assessment is to understand what the organization does with data; measure its current data management capabilities and capacity. What is it?
Data Management Maturity Assessment
56
This readiness assessment will measure the capacity for the organization to change and help identify potential resistance points.
Capacity to Change Assessment
57
This assessment examines how well the organization aligns uses of data with business strategy.
Business alignment Assessment
58
This assessment characterizes the organization’s ability to work together in the management and use of data.
Collaboration Readiness Assessment
59
Name 4 touch points that support alignment and cohesiveness of an enterprise data governance and data management approach in areas outside the direct authority of the Chief Data Officer.
* Procurement and Contracts * Budget and Funding * Regulatory Compliance * SDLC / development framework
60
What are the elements of a Data Governance Strategy?
* Charter * Operating framework and accountabilities * Implementation roadmap * Plan for operational success
61
What areas should be considered when constructing an organization’s operating model?
* Value of data to the organization: If an organization sells data, obviously DG has a huge business impact. * Business model: Decentralized business vs. centralized, local vs. international, etc. * Cultural factors: Such as acceptance of discipline and adaptability to change. * Impact of regulation
62
Hare are goals, policies, and principles drafted, formalized and approved?
Goals, principles, and policies are typically drafted by either by data management professionals, business policy staff, or a combination, under the auspices of data governance. Next, Data Stewards and management review and refine them. Then, the Data Governance Council (or similar body) conducts the final review, revision, and adoption.
63
What is the vehicle for bringing about change in an organization’s systems and processes?
Organizational Change Management (OCM)
64
A change management program supporting formal Data Governance should focus communications on
* 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
65
_________is the process for identifying, quantifying, prioritizing, and resolving data governance-related issues.
Issue management
66
Data governance requires these 6 control mechanisms and procedures.
* Identifying, capturing, logging, tracking, and updating issues * Assignment and tracking of action items * Documenting stakeholder viewpoints and resolution alternatives * Determining, documenting, and communicating issue resolutions * Facilitating objective, neutral discussions where all viewpoints are heard * Escalating issues to higher levels of authority
67
_________refer to Principles for Effective Risk Data Aggregation and risk reporting, a wide ranging set of regulations for banks. Since 2006, financial institutions doing business in European Union countries are required to report standard information proving liquidity.
BCBS 239 (Basel Committee on Banking Supervision) and Basel II
68
What are data management standards?
A standard is defined as “something that is very good and that is used to make judgments about the quality of other things” or as “something set up and established by authority as a rule for the measure of quantity, weight, extent, value, or quality.”31 Standards help define quality because they provide a means of comparison.
69
What are data management procedures?
Data management procedures are the documented methods, techniques, and steps followed to accomplish specific activities that produce certain outcomes and supporting artifacts. Like policies and standards, procedures vary widely across organizations. As is the case with data standards, procedural documents capture organizational knowledge in an explicit form. Procedural documentation is usually drafted by data management professionals.
70
What is a business glossary? And what is it's objective?
A glossary is a means of defining and sharing a vocabulary within the organization. Developing and documenting standard data definitions reduces ambiguity and improves communication. Definitions must be clear, rigorous in wording, and explain any exceptions, synonyms or variants. * Enable common understanding of the core business concepts and terminology * Reduce the risk that data will be misused due to inconsistent understanding of the business concepts * Improve the alignment between technology assets (with their technical naming conventions) and the business organization * Maximize search capability and enable access to documented institutional knowledge
71
The enterprise data model should be developed and maintained jointly by ______ and ______working together in subject area teams.
data architects and Data Stewards
72
True or False: The DGC sponsors and approves data architecture artifacts, such as a business-oriented enterprise data model.
True
73
How do some organizations begin data asset valuation?
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 cost of closing or preventing gaps can be used to estimate of business value of the missing data. From there, the organization can develop models to estimate the value of the information that does exist.
74
One goal of the data governance organization is to _______ in a range of processes behaviors related to managing data as an asset.
embed
75
What tools help a data governance program manage its work and data effectively?
Online Presences / Website Business Glossary Workflow tools Document Management Tools Data Governance Scorecard
76
What tools will the DG team need to be flexible and adjust its approach as conditions shift and effective communicate changes?
* Business / DG strategy map: This map connects DG activity with business needs. Periodically measuring and communicating how DG is helping the business is vital to obtain ongoing support for the program. * DG roadmap: The roadmap to DG should not be rigid. It should be adapted to changes in business environment or priorities. * Ongoing business case for DG: The business case must be adjusted periodically to reflect changing priorities and financial realities of the organization. * DG metrics: Metrics will need to grow and change as the DG program matures.
77
What metrics help a DG program measure value?
o Contributions to business objectives o Reduction of risk o Improved efficiency in operations
78
What metrics help a DG program measure effectiveness?
o Achievement of goals and objectives o Extent stewards are using the relevant tools o Effectiveness of communication o Effectiveness of education/training o Speed of change adoption
79
What metrics help a DG program measure sustainability?
o Performance of policies and processes (i.e., are they working appropriately?) o Conformance to standards and procedures (i.e., are staff following the guidance and changing behavior as necessary?)
80
What are 3 motivations for Data Governance?
Reactive (ex: Data breach) Preemptive (new competitor or threat) Proactive (improve capabilities to resolve risk and data issues)

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