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DMBOK V2 > Subject Area Goals (Reverse) > Flashcards

Subject Area Goals (Reverse) Flashcards

1
Q

Discover relationships between data and the business.

A

<p><strong>Big Data and Data Science</strong></p>

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2
Q

Support the iterative integration of data source(s) into the enterprise.

A

<p><strong>Big Data and Data Science</strong></p>

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3
Q

Discover and analyze new factors that might affect the business.

A

<p><strong>Big Data and Data Science</strong></p>

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4
Q

Publish data using visualization techniques in an appropriate, trusted, and ethical manner.

A

<p><strong>Big Data and Data Science</strong></p>

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5
Q

Develop a governed approach to make data fit for purpose based on data consumers’ requirements.

A

<p><strong>Data Quality</strong></p>

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6
Q

Define standards, requirements, and specifications for data quality controls as part of the data lifecycle.

A

<p><strong>Data Quality</strong></p>

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7
Q

Define and implement processes to measure, monitor, and report on data quality levels.

A

<p><strong>Data Quality</strong></p>

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8
Q

Identify and advocate for opportunities to improve the quality of data, through process and system improvements.

A

<p><strong>Data Quality</strong></p>

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9
Q

Provide organizational understanding of business terms and usage.

A

<p><strong>Metadata Management</strong></p>

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10
Q

Collect and integrate metadata from diverse sources.

A

<p><strong>Metadata Management</strong></p>

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11
Q

Provide a standard way to access metadata.

A

<p><strong>Metadata Management</strong></p>

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12
Q

Ensure metadata quality and security.

A

<p><strong>Metadata Management</strong></p>

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13
Q

To build and maintain the technical environment and technical and business processes needed to deliver integrated data in support of operational functions, compliance requirements, and business intelligence activities.

A

<p><strong>Data Warehousing and Business Intelligence</strong></p>

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14
Q

To support and enable effective business analysis and decision making by knowledge workers.

A

<p><strong>Data Warehousing and Business Intelligence</strong></p>

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15
Q

Enable sharing of information assets across business domains and applications within an organization.

A

<p><strong>Reference and Master Data</strong></p>

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16
Q

Provide authoritative source of reconciled and quality-assessed master and reference data.

A

<p><strong>Reference and Master Data</strong></p>

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17
Q

Lower cost and complexity through use of standards, common data models, and integration patterns.

A

<p><strong>Reference and Master Data</strong></p>

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18
Q

To comply with legal obligations and customer expectations regarding Records management.

A

<p><strong>Document and Content Management</strong></p>

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19
Q

To ensure effective and efficient storage, retrieval, and use of Documents and Content.

A

<p><strong>Document and Content Management</strong></p>

20
Q

To ensure integration capabilities between structured and unstructured Content.

A

<p><strong>Document and Content Management</strong></p>

21
Q

Provide data securely, with regulatory compliance, in the format and timeframe needed.

A

<p><strong>Data Integration and Interoperability</strong></p>

22
Q

Lower cost and complexity of managing solutions by developing shared models and interfaces.

A

<p><strong>Data Integration and Interoperability</strong></p>

23
Q

Identify meaningful events and automatically trigger alerts and actions.

A

<p><strong>Data Integration and Interoperability</strong></p>

24
Q

Support business intelligence, analytics, master data management, and operational efficiency efforts.

A

<p><strong>Data Integration and Interoperability</strong></p>

25
Q

Enable appropriate, and prevent inappropriate, access to enterprise data assets.

A

<p><strong>Data Security</strong></p>

26
Q

Understand and comply with all relevant regulations and policies for privacy, protection, andconfidentiality.

A

<p><strong>Data Security</strong></p>

27
Q

Ensure that the privacy and confidentiality needs of all stakeholders are enforced and audited.

A

<p><strong>Data Security</strong></p>

28
Q

Manage availability of data throughout the data lifecycle.

A

<p><strong>Data Storage and Operations</strong></p>

29
Q

Ensure the integrity of data assets.

A

<p><strong>Data Storage and Operations</strong></p>

30
Q

Manage performance of data transactions.

A

<p><strong>Data Storage and Operations</strong></p>

31
Q

To confirm and document an understanding of different perspectives, which leads to applications that more closely align with current and future business requirements, and creates a foundation to successfully complete broad-scoped initiatives such as master data management and data governance programs.

A

<p><strong>Data Modeling and Design</strong></p>

32
Q

Identify data storage and processing requirements.

A

<p><strong>Data Architecture</strong></p>

33
Q

Design structures and plans to meet the current and long-term data requirements of the enterprise.

A

<p><strong>Data Architecture</strong></p>

34
Q

Strategically prepare organizations to quickly evolve their products, services, and data to take advantage of business opportunities inherent in emerging technologies.

A

<p><strong>Data Architecture</strong></p>

35
Q

Enable an organization to manage its data as an asset.

A

<p><strong>Data Governance</strong></p>

36
Q

Define, approve, communicate, and implement principles, policies, procedures, metrics, tools, and responsibilities for data management.

A

<p><strong>Data Governance</strong></p>

37
Q

Monitor and guide policy compliance, data usage, and management activities.

A

<p><strong>Data Governance</strong></p>

38
Q

To define ethical handling of data in the organization

A

<p><strong>Data Ethics</strong></p>

39
Q

To educate staff on the organization risks of improper data handling

A

<p><strong>Data Ethics</strong></p>

40
Q

To change/instill preferred culture and behaviors on handling data.

A

<p><strong>Data Ethics</strong></p>

41
Q

To monitor regulatory environment, measure, monitor, and adjust organization approaches for ethics in data.

A

<p><strong>Data Ethics</strong></p>

42
Q

Understanding and supporting the information needs of the enterprise and its stakeholders, includingcustomers, employees, and business partners

A

<p><strong>Data Management</strong></p>

43
Q

Capturing, storing, protecting, and ensuring the integrity of data assets

A

<p><strong>Data Management</strong></p>

44
Q

Ensuring the quality of data and information

A

<p><strong>Data Management / Data Quality</strong></p>

45
Q

Ensuring the privacy and confidentiality of stakeholder data

A

<p><strong>Data Management</strong></p>

46
Q

Preventing unauthorized or inappropriate access, manipulation, or use of data and information

A

<p><strong>Data Management / Data Security</strong></p>

47
Q

Ensuring data can be used effectively to add value to the enterprise

A

<p><strong>Data Management</strong></p>

DMBOK V2 (6 decks)

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