ANSWERS
Question:
1. Data Management
Answer:
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.
Question:
2. Data Management Professional
Answer:
Person who works in any facet of data management to meet strategic organizational goals.
Question:
3. Data AKA
Answer:
currency, life blood, new oil
Question:
4. Value
Answer:
Difference between the cost and benefit of an asset
Question:
5. Data
Answer:
asset or resource that can be owned or controlled. information that has been stored in digital form.
Question:
6. Data Quality
Answer:
2nd step to good data management. measure of the condition of data based on factors such as accuracy,
completeness, consistency, reliability and whether it's up to date.
Question:
7. Data Architecture
Answer:
the structure of an organization's logical and physical data assets and data management resources
Question:
8. Risk
Answer:
low quality data (inaccurate, incomplete, or out-of-date); data being misused or misunderstood
,Question:
9. Data Security
Answer:
authorization and authentication, processes and controls on who accesses data and when as well as logs on
usage and how data is processed
Question:
10. lifecycle
Answer:
processes that create or obtain data, move, transform, and store data; and enable it to be maintained and
shared, and those that use and apply it, as well as those that dispose of it.
Question:
11. Data Ethics
Answer:
branch of ethics that evaluates data practices—collecting, generating, analyzing and disseminating data,
both structured and unstructured—that have the potential to adversely impact people and society.
Question:
12. Information gaps
Answer:
liabilities with impacts on operational effectiveness and profitability; difference between what data is
needed and what is available
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13. Cross-functional management
Answer:
collaboration across different places in the organization where data is generated, stored, and accessed
across different phases of the data lifecycle
Question:
14. Challenges of Data Management
Answer:
data quality, data valuation, effective metadata, cross-functional management, enterprise perspective,
management of the lifecycle, and classification and control of data
Question:
15. Data Governance
Answer:
The first step to good data management. process of managing the availability, usability, integrity and
security of the data in enterprise systems, based on internal data standards and policies that also control
data usage
Question:
16. Data Management Principles
,Answer:
data is an asset, value of data should be expressed in economic terms, must manage the quality of data,
manage metadata, it takes planning, cross-functional, enterprise perspective, must account for range of
perspectives, lifecycle management, differing lifecycles, managing risks, drive IT decisions, leadership
commitment
Question:
17. Benefits of High Quality Data
Answer:
Improved customer experience, higher productivity, reduced risk, ability to act on opportunities, increased
revenue, competitive advantage gained from insights
Question:
18. Plans for better data
Answer:
ways data connects disparate processes, relationship between processes and the technology that supports
them, design and architecture of systems and the data they produce, ways data might advance
organizational strategy
Question:
19. Skills for cross-functional design
Answer:
design skills, technical, data analysis, analytic, language, strategic thinking
Question:
20. Enterprise perspective
Answer:
making disparate data from different departments or different representational choices of data fit together
in a common sense way so it is usable by a range of data customers.
Question:
21. Implications of management in data lifecycle
Answer:
creation and usage are the most critical points in the lifecycle, data quality throughout, metadata quality,
data security, focus on most critical data, minimize redundant data
Question:
22. classifications of data
Answer:
types - transactional, reference, master, meta, category, resource, event, detailed transaction content -
domains, subject area, format, or level of protection how/where it is accessed
Question:
23. Critical component for data management success
Answer:
committed leadership and the involvement of everyone at all levels of the organization
, Question:
24. Necessary for data management success
Answer:
vision, planning, and willingness to change
Question:
25. Data Strategy
Answer:
high-level course of action that includes business plans to use information to competitive advantage and
support enterprise goals.
Question:
26. Where data strategy comes from
Answer:
understanding of data needs in the business strategy, what the organization needs, how it will get the data,
and how it will manage and utilize it
Question:
27. Data management program strategy
Answer:
plan for maintaining and improving the quality of data, data integrity, access and security while mitigating
known and implied risks
Question:
28. Components of data strategy
Answer:
vision, summary, guiding principles, values and management perspectives; mission and long-term goals,
measures of data management success, SMART short-term, roles and responsibilities and rights, program
components and initiatives, program of work and scope boundaries, implementation roadmap with projects
and action item
Question:
29. Deliverables from strategic planning
Answer:
Charter (vision, goals, business case, guiding principles, measures of success and factors, risks, operating
model), Scope (goals and objectives for planning horizon, roles, responsibilities, leaders achieving these),
Roadmap (programs, projects, assignments, tasks, and milestones)
Question:
30. Data Management Frameworks
Answer:
Strategic Alignment Model, Amsterdam Information Model, DAMA-DMBOK, Aiken
Question:
31. Knowledge Areas for DAMA-DM- BOK Framework