DAMA DMBOK CDMP > Data Management > Flashcards

Data Management Flashcards

(54 cards)

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1
Q

What is the definition of Data Management?

A

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.

It requires intention, planning, coordination, and commitment.

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2
Q

Who is considered a Data Management Professional?

A

Any person who works in any facet of data management, including roles from technical management to strategic business.

Roles include database administrators, Data Stewards, Data Strategists, and Chief Data Officers.

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3
Q

List the goals of data management within an organization.

A
  • Understanding and supporting information needs
  • Capturing, storing, protecting data
  • Ensuring data quality
  • Ensuring privacy and confidentiality
  • Preventing unauthorized access
  • Adding value to the enterprise

These goals support organizational stakeholders, including customers and employees.

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4
Q

True or false: Data is only considered an asset when it is digitized.

A

FALSE

Data management principles apply to data captured on paper as well as in databases.

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5
Q

What does Metadata refer to in data management?

A

Data about data, which is necessary for understanding and managing data.

Metadata originates from processes related to data creation, processing, and use.

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6
Q

What are the characteristics of data that make it different from other assets?

A
  • Not tangible
  • Durable
  • Easy to copy and transport
  • Not consumed when used
  • Dynamic and can be used for multiple purposes

These characteristics complicate the management and valuation of data.

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7
Q

What is the primary driver for data management?

A

To enable organizations to get value from their data assets.

Similar to effective management of financial and physical assets.

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8
Q

Fill in the blank: Data has been called the __________ of information.

A

raw material

Information is often described as data in context.

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9
Q

What is the relationship between data and information?

A

Data is a form of information and information is a form of data.

They are intertwined and dependent on each other.

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10
Q

List the challenges of data management.

A
  • Data differs from other assets
  • Difficulty in measuring data’s monetary value
  • Defining data ownership
  • Protecting against misuse of data
  • Managing risks associated with data redundancy

These challenges affect how data is managed and valued.

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11
Q

What is meant by data lifecycle management?

A

Managing data throughout its lifecycle, recognizing that data begets more data.

Data management practices need to account for the complexities of the data lifecycle.

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12
Q

What is the DAMA Data Management Framework?

A

A framework that provides context for the work carried out by data management professionals within various Data Management Knowledge Areas.

It outlines principles and challenges related to data management.

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13
Q

True or false: Organizations must manage data as an asset to derive ongoing value.

A

TRUE

Effective management requires intention and professional discipline.

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14
Q

What is the significance of being a data-driven organization?

A

Organizations must use data to make decisions rather than relying on gut feelings.

This includes recognizing the need for efficient data management.

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15
Q

What are the key aspects of data management?

A
  • Protecting against misuse of data
  • Managing risk associated with data redundancy
  • Defining and enforcing standards for Data Quality

These aspects are crucial for ensuring the integrity and usability of data within organizations.

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16
Q

Data is considered a meta-asset because it describes what?

A

Other assets

Data provides foundational insights about an organization’s operations and resources.

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17
Q

What are some cost categories associated with data valuation?

A
  • Cost of obtaining and storing data
  • Cost of replacing data if lost
  • Impact to the organization if data is missing
  • Cost of risk mitigation
  • Cost of improving data
  • Benefits of higher quality data
  • Expected revenue from innovative uses of data

These categories help organizations assess the value of their unique data.

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18
Q

True or false: The value of data is contextual and temporal.

A

TRUE

The value of data can vary significantly based on the organization and time.

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19
Q

What does metadata include in the context of data management?

A
  • Business Metadata
  • Technical Metadata
  • Operational Metadata
  • Metadata embedded in Data Architecture
  • Data integration standards

Metadata is essential for understanding and managing data effectively.

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20
Q

Data management is considered a cross-functional process because it involves what?

A
  • Design skills
  • Technical skills
  • Data analysis skills
  • Analytic skills
  • Language skills
  • Strategic thinking

Collaboration across various skill sets is necessary for effective data management.

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21
Q

What is the data lifecycle?

A
  • Creation or obtaining data
  • Moving, transforming, and storing data
  • Maintaining and sharing data
  • Using or applying data
  • Disposing of data

Understanding the data lifecycle is crucial for effective data management.

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22
Q

What are some costs associated with poor data quality?

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A
  • Scrap and rework
  • Work-arounds
  • Organizational inefficiencies
  • Low job satisfaction
  • Customer dissatisfaction
  • Compliance costs or fines

Poor data quality can lead to significant financial losses for organizations.

23
Q

What are the benefits of high-quality data?

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A
  • Improved customer experience
  • Higher productivity
  • Reduced risk
  • Increased revenue
  • Competitive advantage

High-quality data can significantly enhance organizational performance.

24
Q

What must organizations do to ensure data quality throughout the data lifecycle?

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A
  • Plan for data quality
  • Manage metadata quality
  • Ensure data security

Data quality management is an ongoing process that requires attention at every stage.

25
Different types of data have different **lifecycle management requirements**. Name some classifications of data.
* Transactional data * Reference Data * Master Data * Metadata * Resource data * Event data ## Footnote Understanding these classifications helps in managing data effectively.
26
Data represents both **value** and **risk**. What are some risks associated with low-quality data?
* Inaccurate information * Misunderstanding of data * Misuse of data ## Footnote Organizations must recognize and mitigate these risks to leverage data effectively.
27
What do **privacy regulations** cover?
Processing of data about people across a wide range of industries and jurisdictions ## Footnote These regulations are increasingly important as consumers become more aware of how their data is used.
28
What is expected to be seen on the **risk register** regarding information management?
Information as an asset with appropriate mitigations and controls ## Footnote This reflects the regulatory environment's expectations for data management.
29
True or false: Consumers expect smoother operations but do not care about the protection of their information.
FALSE ## Footnote Consumers expect both efficiency and respect for their privacy.
30
What are the **challenges** of managing data?
* Organizations often confuse data and information technology * Many do not know what data they have * They underestimate the work involved with data management ## Footnote These challenges highlight the need for committed leadership in data management.
31
What is the role of a **Chief Data Officer (CDO)**?
* Lead data management initiatives * Enable organizations to leverage data assets * Lead cultural change for a strategic approach to data ## Footnote The CDO's role is crucial for successful data management.
32
A **data strategy** should include plans to use information for what purpose?
Competitive advantage and support enterprise goals ## Footnote It must align with the business strategy's data needs.
33
What are the components of a **data management strategy**?
* Compelling vision for data management * Summary business case * Guiding principles * Mission and long-term goals * Proposed measures of success * Short-term objectives * Descriptions of roles and responsibilities * Prioritized program of work * Implementation roadmap ## Footnote These components help in maintaining and improving data quality and integrity.
34
What does the **DAMA Wheel** define?
Data Management Knowledge Areas ## Footnote It places data governance at the center, indicating its importance.
35
What are the **phases** in Peter Aiken’s framework for data management?
* Phase 1: Purchase of an application with database capabilities * Phase 2: Challenges with data quality * Phase 3: Implementation of Data Governance * Phase 4: Leveraging benefits of well-managed data ## Footnote This framework illustrates the progression organizations go through in data management.
36
What is the purpose of a **data governance program**?
To enable organizations to be data-driven ## Footnote It establishes strategy, principles, policies, and stewardship practices for data management.
37
What are the **core activities** in the DAMA Data Management Framework?
* Metadata Management * Data Quality Management * Data structure definition (architecture) ## Footnote These activities are essential for effective data management.
38
Fill in the blank: A **data management strategy** requires a supporting _______.
Data Management program strategy ## Footnote This plan is crucial for maintaining data quality and integrity.
39
What are the **main areas** of data management mentioned in the text?
* Data Governance * Data Architecture * Data Modeling and Design * Data Storage and Operations * Data Security * Data Integration and Interoperability * Document and Content Management ## Footnote These areas encompass the essential activities and responsibilities within data management.
40
What does **Data Governance** provide for data management?
Direction and oversight ## Footnote It establishes a system of decision rights over data that accounts for the needs of the enterprise.
41
The **DAMA-DMBOK** serves as a fundamental reference guide for which certification?
CDMP (Certified Data Management Professional) ## Footnote It supports the mission of DAMA by providing a functional framework for enterprise data management practices.
42
What is the purpose of **Data Architecture**?
Defines the blueprint for managing data assets ## Footnote It aligns with organizational strategy to establish strategic data requirements and designs.
43
True or false: **Data Quality** includes planning and implementation of quality management techniques.
TRUE ## Footnote It aims to measure, assess, and improve the fitness of data for use within an organization.
44
What does **Data Modeling and Design** involve?
Discovering, analyzing, representing, and communicating data requirements ## Footnote This is done in a precise form called the data model.
45
Fill in the blank: **Data Security** ensures that data privacy and confidentiality are maintained, that data is not breached, and that data is accessed _______.
appropriately ## Footnote This is crucial for protecting sensitive information.
46
What does **Document and Content Management** focus on?
Managing the lifecycle of data and information found in unstructured media ## Footnote This includes documents needed to support legal and regulatory compliance requirements.
47
What is the role of **Metadata** in data management?
Enables access to high quality, integrated Metadata ## Footnote This includes definitions, models, data flows, and other critical information.
48
What is the significance of **Data Handling Ethics**?
Guides informed, socially responsible decisions about data ## Footnote Awareness of ethics in data collection, analysis, and use is essential for data management professionals.
49
What does **Data Warehousing and Business Intelligence** encompass?
Planning, implementation, and control processes for decision support data ## Footnote It enables knowledge workers to derive value from data through analysis and reporting.
50
What is the **DAMA Wheel**?
A framework representing the eleven Knowledge Areas of data management ## Footnote It serves as a visual tool for understanding the scope of data management activities.
51
What is the **intention** behind presenting different visual depictions of the DAMA Data Management Framework?
To provide additional perspective and open discussion ## Footnote This helps in applying the concepts presented in DMBOK.
52
What are **Knowledge Areas** in the context of data management?
Scope and context of sets of data management activities ## Footnote They intersect with each other and with other organizational functions.
53
What is the **goal** of the DAMA organization?
To address challenges in data management ## Footnote It aims to support professionals in implementing effective data management practices.
54
What does **Data Integration and Interoperability** include?
Processes related to the movement and consolidation of data ## Footnote This occurs within and between data stores, applications, and organizations.
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