DAMA Online Training Dumps, DAMA Online Training Real Exam Questions

There are many way to prepare for your DMF-1220 Data Management Fundamentals exam.After using Exam4Training DAMA DMF-1220 Data Management Fundamentals Online Training, you will accept that it takes you a step closer to the CDMP Certification DMF-1220 exam success. The DAMA DMF-1220 Data Management Fundamentals Online Training covers all the aspects of the real DMF-1220 exam. Exam4Training has always verified and updated DMF-1220 questions and answers, which helps you to prepare your DAMA DMF-1220 exam with less effort in short time.

Page 1 of 20

1. Improving data quality requires a strategy that accounts for the work that needs to be done and the way people will execute it.

TRUE

FALSE

2. A data governance strategy defines the scope and approach to governance efforts. Deliverables include:

Charter

Operating framework and accountabilities

Implementation roadmap

Plan for operational success

All of the above

None of the above

3. Data stewardship is the least common label to describe accountability and responsibility for data and processes to ensure effective control and use of data assets.

TRUE

FALSE

4. A hacker is a person who finds unknown operations and pathways within complex computer system. Hackers are only bad.

TRUE

FALSE

5. Orchestration is the term used to describe how multiple processes are organized and executed in a system.

TRUE

FALSE

6. A dimensional physical data model is usually a star schema, meaning there is one structure for each dimension.

FALSE

TRUE

7. Many people assume that most data quality issues are caused by data entry errors. A more sophisticated understanding recognizes that gaps in or execution of business and technical processes cause many more problems that mis-keying.

TRUE

FALSE

8. Sample value metrics for a data governance program include:

Reduction of risk

Improved efficiency in operations

Effectiveness of education

Achievements of goals and objectives

Contributions to business objectives

Effectiveness of communication

9. RACI is an acronym that is made up of the following terms.

Control

Responsible

Accountable

Informed

Reliable

Consulted

10. SLA Stands for:

Service Level Agreement

System Lifecycle Audit

System Latitude Audit

Service Lifecycle Audit

Page 2 of 20

11. Different types of product Master Data solutions include:

People Lifecycle Product Management (PLPM)

Product data in Manufacturing Execution Systems (MES)

None of the above

Product Data in Enterprise Resource Planning (ERP)

Product Lifecycle Management (PLM)

12. A business driver for Master Data Management program is managing data quality.

TRUE

FALSE

13. Please select the transition phases in Bridges’ Transition process:

The neutral zone

The new beginning

The ending

The transition

The translation

The game

14. The business glossary should capture business terms attributes such as:

Lineage

Utilization

Common misunderstanding in terms

System development

Algorithms to supporting definitions

All of the above

15. Use business rules to support Data Integration and Interoperability at various points, to:

Direct the flow of data in the organization

Monitor the organization’s operational data

Software alerts when events are triggered

Direct when to automatically trigger events and alerts

Consistency in allocation event resources

None of the above

16. Data professional should not balance the short-term versus long-term business interests.

TRUE

FALSE

17. Most document programs have policies related to:

Scope and compliance audits

Proper destruction of records

Proper construction of records

Identification and protection of vital records

Partition tolerance

All of the above

18. The Data Warehouse (DW) is a combination of three primary components: An integrated decision support database, related software programs and business intelligence reports.

FALSE

TRUE

19. Data lineage is useful to the development of the data governance strategy.

TRUE

FALSE

20. DAMA International’s Certified Data Management Professional (CDMP) certification required that data management professionals 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.

TRUE

FALSE

Page 3 of 20

21. Functionality-focused requirements associated with a comprehensive metadata solution, include:

Synchronization

Structure

None of the above

History

Volatility

Access rights

22. While the focus of data quality improvement efforts is often on the prevention of errors, data quality can also be improved through some forms of data processing.

TRUE

FALSE

23. Valuation information, as an example of data enrichment, is for asset valuation, inventory and sale.

TRUE

FALSE

24. All metadata management solutions include architectural layers including:

Metadata Quality Assurance Testing

Metadata integration

Metadata usage

Metadata delivery

Metadata control and management

None of the above

25. An input in the Metadata management context diagram does not include:

Business requirements

Business metadata

Technical metadata

Metadata standards

Process Metadata

26. A deliverable in the data architecture context diagram includes an implementation roadmap.

TRUE

FALSE

27. Location Master Data includes business party addresses and business party location, as well as facility addresses for locations owned by organizations.

TRUE

FALSE

28. Some ways to measure value of data include:

Replacement cost

Market value

Selling Data

Risk cost

Identified opportunities

All of the above

29. Match rules for different scenarios require different workflows, including:

Consistency rules

Duplicate identification match rules

Match-merge rules

Match-split rules

Match-link rules

All of the above

30. The IT security policy provides categories for individual application, database roles, user groups and information sensitivity.

TRUE

FALSE

Page 4 of 20

31. Data profiling examples include:

Counts of null

Max/Min value

Max/Min length

Frequency distribution

Data type and format

None of the above

32. Information gaps represent enterprise liabilities with potentially profound impacts on operational effectiveness and profitability.

TRUE

FALSE

33. When constructing an organization’s operating model cultural factors must be taken into consideration.

TRUE

FALSE

34. What model is the highest level model within the enterprise data model?

Logical model

Physical model

Conceptual model

Subject Area model

35. Data Integration and Interoperability (DII) describes processes related to the movement and consolidation of data within and between data stores, applications and organizations.

TRUE

FALSE

36. Examples of concepts that can be standardized within the data architecture knowledge area include:

Enterprise data models

System naming conventions

None of the above

Data security standards

Data quality rules

Tool standards

37. Business metadata focuses largely on the content and condition of the data and includes details related to data governance.

TRUE

FALSE

38. Reference and Master Data Management follow these guiding principles:

Quality

Stewardship

Authority

Ownership

Exclusivity

Inclusivity

39. Self-service is a fundamental delivery channel in the BI portfolio.

TRUE

FALSE

40. The Shewhart chart contains the following elements:

Plan

Utilization

Check

Act

All of the above

Page 5 of 20

41. The warehouse has a set of storage areas, including:

Staging area

Data marts

Consistent object attributes

Operational data store (ODS)

Cubes

Central warehouse

42. Data quality management is a key capability of a data management practice and organization.

TRUE

FALSE

43. Data and text mining use a range of techniques, including:

Profiling

Application reduction

Association

Data reduction

Clustering

All of the above

44. Examples of technical metadata include:

Column Properties

Access permissions

Internal

Conceptual

ETL job details

45. CMDB provide the capability to manage and maintain Metdata specifically related to the IT assets, the relationships among them, and contractual details of the assets.

TRUE

FALSE

46. Data Warehouse describes the operational extract, cleansing, transformation, control and load processes that maintain the data in a data warehouse.

FALSE

TRUE

47. Improving an organization’s ethical behaviour requires an informal Organizational Change Management (OCM) process.

TRUE

FALSE

48. Veracity refers to how difficult the data is to use or to integrate.

TRUE

FALSE

49. Please select the correct General Accepted Information Principles:

Asset Principle

Audit Principle

Due Diligence Principle

Going Concern Principle

Ethical Principle

All of the above

50. Corporate Information Factory (CIF) components include:

Data marts

Objectives

Operational Reports

Reduction of risk

Staging Area

Contributions to business objectives

Page 6 of 20

51. Inputs in the data quality context diagram include:

Data stores

Data lakes

Business requirements

Data quality expectations

52. The data warehouse and marts differ from that in applications as the data is organized by subject rather than function.

TRUE

FALSE

53. A data dictionary is necessary to support the use of a DW.

TRUE

FALSE

54. Architects seek to design in a way that brings value to an organisation. To reach these goals, data architects define and maintain specifications that:

Align data architecture with enterprise strategy and business architecture

Provide a standard business vocabulary for data and components

Outline high-level integrated designs to meet these requirements.

Integrate with overall enterprise architecture roadmap

Define the current state of data in the organization.

Express strategic data requirements

55. A limitation of the centralized metadata repository approach is it may be less expensive.

TRUE

FALSE

56. Big data primarily refers specifically to the volume of the data.

TRUE

FALSE

57. The accuracy dimension has to do with the precision of data values.

TRUE

FALSE

58. BI tool types include:

BPM

Operational reporting

Data lake extraction

Diagnostic, self-service analytics

Descriptive, self-service analytics

Reduction of risk

59. The goals of Data Integration and Interoperability include:

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

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

Managing the availability of data throughout the data lifecycle

Provide the starting point for customizations, integration or even replacement of an application

Identify meaningful events and automatically trigger alerts and actions.

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

60. The Belmont principles that may be adapted for Information Management disciplines, include:

Respect for Persons

Respect for Machines

Beneficence

Criminality

Justice

Page 7 of 20

61. Elements that point to differences between warehouses and operational systems include:

Historical

Data security standards

Subject-orientated

Non-volatile

Data quality

Integrated

62. Please select the correct general cost and benefit categories that can be applied consistently within an organization.

Cost of erasing data from servers

Cost of improving data

What the data could be sold for

Benefit of higher quality data

Cost of replacing data if it were lost

What competitors would pay for data

63. Please select correct term for the following sentence: An organization shall assign a senior executive to appropriate individuals, adopt policies and processes to guide staff and ensure program audibility.

Principle of integrity

Principle of availability

Principle of retention

Principle of accountability

64. Please select the answers that correctly describes where the costs of poor quality data comes from.

Scrap and rework

Organizational conflict

High job satisfaction

High productivity

Reputational costs

Compliance costs

65. The implementation of a Data Warehouse should follow guiding principles, including:

Data Efficiency

One size does not fit all

Contracts

Focus on the business goals

Start with the end in mind

Collaborate

66. A ‘Golden Record’ means that it is always a 100% complete and accurate representation of all entities within the organization.

TRUE

FALSE

67. Data quality issues cannot emerge at any point in the data lifecycle.

FALSE

TRUE

68. SSD is the abbreviation for Solid State Dimension.

TRUE

FALSE

69. Please select valid modelling schemes or notations

NoSQL

Dimensional

Relational

Object-orientated

Fact-based

Matrix-based

70. Consistent input data reduces the chance of errors in associating records. Preparation processes include:

Standardization

Enrichment CValidation

Database management

Page 8 of 20

71. Confirming and documenting understanding of different perspectives facilitate:

Formalization

Normalization

Scope definition

Knowledge retention/documentation

72. The first two steps in the data science process are:

Define Big Data data strategy & Business Need(s)

Choose Data Sources

Develop Data Science Hypotheses and Mehods

Acquire & Ingest Data source(s)

73. DBAs and database architects combine their knowledge of available tools with the business requirements in order to suggest the best possible application of technology to meet organizational goals.

FALSE

TRUE

74. A synonym for transformation in ETL is mapping. Mapping is the process of developing the lookup matrix from source to target structures, but not the result of the process.

TRUE

FALSE

75. Temporal aspects usually include:

Valid time

Transmitting time

Transaction time

Value time

76. Three data governance operating models types include:

Centralized

Decentralized

Feathered

Federated

Replicated

Duplicated

77. CMA is an abbreviation for Capability Maturity Assessment.

TRUE

FALSE

78. Business people must be fully engaged in order to realize benefits from the advanced analytics.

TRUE

FALSE

79. As an often-overlooked aspects of basic data movement architecture, Process controls include:

Consistency logging

Exception logs

Database activity logs

Alerts

Exception logs

All of the above

80. There are several reasons to denormalize data. The first is to improve performance by:

Creating smaller copies of fata to reduce costly run-time calculations and/or table scans of large tables.

None of the above

Pre-calculating and sorting costly data calculations to avoid runt-time system resource competition.

Making tables more readable when no foreign key exists

Combining data from multiple other tables in advance to avoid costly run-time joins

All of the above

Page 9 of 20

81. Vulnerability is defined as:

a patch in a system that allows it to be successfully unpatched and compromised.

being highly data risk rated

a strength in a system that allows external stakeholders to view data records.

a weakness or defect in a system that allows it to be successfully attacked and compromised.

82. Data security issues, breaches and unwarranted restrictions on employee access to data cannot directly impact operational success.

TRUE

FALSE

83. Some document management systems have a module that may support different types of workflows such as:

Quality Assurance Testing (QA)

Manual workflows that indicate where the user send the document

User Acceptance Testing (UAT)

Dynamic rules that allow for different workflows based on content

All of the above

None of the above

84. Within the Data Handling Ethics Context Diagram a key deliverable is the Ethical Data Handling Strategy.

TRUE

FALSE

85. With reliable Metadata an organization does not know what data it has, what the data represents and how it moves through the systems, who has access to it, or what it means for the data to be of high quality.

TRUE

FALSE

86. The deliverables in the data architecture context diagram include:

Data flows

Enterprise data

Implementation roadmap

Data Value Chains

None of the above

All of the above

87. The primary goal of data management capability assessment is to evaluate the current state of critical data management activities in order to plan for improvement.

TRUE

FALSE

88. Master data management includes several basic steps, which include: Develop rules for accurately matching and merging entity instances.

TRUE

FALSE

89. The four main types of NoSQL databases are:

Document

Row-orientated

Graph

Strategic

Key-value

Column-orientated

90. The most common drivers for initiating a Mater Data Management Program are:

Metadata insecurity

Managing data quality

Reducing risk

Managing the costs of data integration

Meeting organizational data requirements

Reducing latency

Page 10 of 20

91. The implementation of a Data Warehouse should follow these guiding principles:

Managing performance of data assets

Focus on the business goals

Managing the availability of data throughout the data lifecycle

Start with the end in mind

Managing the performance of data transactions

Collaborate

92. Data architect: A senior analyst responsible for data architecture and data integration.

TRUE

FALSE

93. A Data Management Maturity Assessment (DMMA) can be used to evaluate data management overall, or it can be used to focus on a single Knowledge Area or even a single process.

TRUE

FALSE

94. Key processing steps for MDM include:

Data model management

Data acquisition

Data validation, standardization and enrichment

Entity resolution

Data sharing and stewardship

None of the above

95. The database administrator (DBA) is the most established and the most widely adopted data professional role.

TRUE

FALSE

96. The operational data quality management procedures depend on the ability to measure and monitor the applicability of data.

FALSE

TRUE

97. Advantages if a centralized metadata repository include:

Quick metadata retrieval

None of the above

Combining data from multiple other tables in advance to avoid costly run-time joins

All of the above

High availability

Low latency, since it is independent of the source systems

98. A goal of a Reference and Master Data Management program include enabling master and reference data to be shared across enterprise functions and applications.

FALSE

TRUE

99. Data professionals involved in Business Intelligence, analytics and Data Science are often responsible for data that describes: who people are; what people do; where people live; and how people are treated. The data can be misused and counteract the principles underlying data ethics.

FALSE

TRUE

100. Small reference data value sets in the logical data model can be implemented in a physical model in three common ways:

Create a matching separate code table

Create a master shared code table

None of the above

Program integration by joining tables

Embed rules or valid codes into the appropriate object’s definition.

Roadmap Development

Page 11 of 20

101. Improving data quality requires a strategy that accounts for the work that needs to be done and the way people will execute it.

TRUE

FALSE

102. A data governance strategy defines the scope and approach to governance efforts. Deliverables include:

Charter

Operating framework and accountabilities

Implementation roadmap

Plan for operational success

All of the above

None of the above

103. Data stewardship is the least common label to describe accountability and responsibility for data and processes to ensure effective control and use of data assets.

TRUE

FALSE

104. A hacker is a person who finds unknown operations and pathways within complex computer system. Hackers are only bad.

TRUE

FALSE

105. Orchestration is the term used to describe how multiple processes are organized and executed in a system.

TRUE

FALSE

106. A dimensional physical data model is usually a star schema, meaning there is one structure for each dimension.

FALSE

TRUE

107. Many people assume that most data quality issues are caused by data entry errors. A more sophisticated understanding recognizes that gaps in or execution of business and technical processes cause many more problems that mis-keying.

TRUE

FALSE

108. Sample value metrics for a data governance program include:

Reduction of risk

Improved efficiency in operations

Effectiveness of education

Achievements of goals and objectives

Contributions to business objectives

Effectiveness of communication

109. RACI is an acronym that is made up of the following terms.

Control

Responsible

Accountable

Informed

Reliable

Consulted

110. SLA Stands for:

Service Level Agreement

System Lifecycle Audit

System Latitude Audit

Service Lifecycle Audit

Page 12 of 20

111. Different types of product Master Data solutions include:

People Lifecycle Product Management (PLPM)

Product data in Manufacturing Execution Systems (MES)

None of the above

Product Data in Enterprise Resource Planning (ERP)

Product Lifecycle Management (PLM)

112. A business driver for Master Data Management program is managing data quality.

TRUE

FALSE

113. Please select the transition phases in Bridges’ Transition process:

The neutral zone

The new beginning

The ending

The transition

The translation

The game

114. The business glossary should capture business terms attributes such as:

Lineage

Utilization

Common misunderstanding in terms

System development

Algorithms to supporting definitions

All of the above

115. Use business rules to support Data Integration and Interoperability at various points, to:

Direct the flow of data in the organization

Monitor the organization’s operational data

Software alerts when events are triggered

Direct when to automatically trigger events and alerts

Consistency in allocation event resources

None of the above

116. Data professional should not balance the short-term versus long-term business interests.

TRUE

FALSE

117. Most document programs have policies related to:

Scope and compliance audits

Proper destruction of records

Proper construction of records

Identification and protection of vital records

Partition tolerance

All of the above

118. The Data Warehouse (DW) is a combination of three primary components: An integrated decision support database, related software programs and business intelligence reports.

FALSE

TRUE

119. Data lineage is useful to the development of the data governance strategy.

TRUE

FALSE

120. DAMA International’s Certified Data Management Professional (CDMP) certification required that data management professionals 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.

TRUE

FALSE

Page 13 of 20

121. Functionality-focused requirements associated with a comprehensive metadata solution, include:

Synchronization

Structure

None of the above

History

Volatility

Access rights

122. While the focus of data quality improvement efforts is often on the prevention of errors, data quality can also be improved through some forms of data processing.

TRUE

FALSE

123. Valuation information, as an example of data enrichment, is for asset valuation, inventory and sale.

TRUE

FALSE

124. All metadata management solutions include architectural layers including:

Metadata Quality Assurance Testing

Metadata integration

Metadata usage

Metadata delivery

Metadata control and management

None of the above

125. An input in the Metadata management context diagram does not include:

Business requirements

Business metadata

Technical metadata

Metadata standards

Process Metadata

126. A deliverable in the data architecture context diagram includes an implementation roadmap.

TRUE

FALSE

127. Location Master Data includes business party addresses and business party location, as well as facility addresses for locations owned by organizations.

TRUE

FALSE

128. Some ways to measure value of data include:

Replacement cost

Market value

Selling Data

Risk cost

Identified opportunities

All of the above

129. Match rules for different scenarios require different workflows, including:

Consistency rules

Duplicate identification match rules

Match-merge rules

Match-split rules

Match-link rules

All of the above

130. The IT security policy provides categories for individual application, database roles, user groups and information sensitivity.

TRUE

FALSE

Page 14 of 20

131. Data profiling examples include:

Counts of null

Max/Min value

Max/Min length

Frequency distribution

Data type and format

None of the above

132. Information gaps represent enterprise liabilities with potentially profound impacts on operational effectiveness and profitability.

TRUE

FALSE

133. When constructing an organization’s operating model cultural factors must be taken into consideration.

TRUE

FALSE

134. What model is the highest level model within the enterprise data model?

Logical model

Physical model

Conceptual model

Subject Area model

135. Data Integration and Interoperability (DII) describes processes related to the movement and consolidation of data within and between data stores, applications and organizations.

TRUE

FALSE

136. Examples of concepts that can be standardized within the data architecture knowledge area include:

Enterprise data models

System naming conventions

None of the above

Data security standards

Data quality rules

Tool standards

137. Business metadata focuses largely on the content and condition of the data and includes details related to data governance.

TRUE

FALSE

138. Reference and Master Data Management follow these guiding principles:

Quality

Stewardship

Authority

Ownership

Exclusivity

Inclusivity

139. Self-service is a fundamental delivery channel in the BI portfolio.

TRUE

FALSE

140. The Shewhart chart contains the following elements:

Plan

Utilization

Check

Act

All of the above

Page 15 of 20

141. The warehouse has a set of storage areas, including:

Staging area

Data marts

Consistent object attributes

Operational data store (ODS)

Cubes

Central warehouse

142. Data quality management is a key capability of a data management practice and organization.

TRUE

FALSE

143. Data and text mining use a range of techniques, including:

Profiling

Application reduction

Association

Data reduction

Clustering

All of the above

144. Examples of technical metadata include:

Column Properties

Access permissions

Internal

Conceptual

ETL job details

145. CMDB provide the capability to manage and maintain Metdata specifically related to the IT assets, the relationships among them, and contractual details of the assets.

TRUE

FALSE

146. Data Warehouse describes the operational extract, cleansing, transformation, control and load processes that maintain the data in a data warehouse.

FALSE

TRUE

147. Improving an organization’s ethical behaviour requires an informal Organizational Change Management (OCM) process.

TRUE

FALSE

148. Veracity refers to how difficult the data is to use or to integrate.

TRUE

FALSE

149. Please select the correct General Accepted Information Principles:

Asset Principle

Audit Principle

Due Diligence Principle

Going Concern Principle

Ethical Principle

All of the above

150. Corporate Information Factory (CIF) components include:

Data marts

Objectives

Operational Reports

Reduction of risk

Staging Area

Contributions to business objectives

Page 16 of 20

151. Inputs in the data quality context diagram include:

Data stores

Data lakes

Business requirements

Data quality expectations

152. The data warehouse and marts differ from that in applications as the data is organized by subject rather than function.

TRUE

FALSE

153. A data dictionary is necessary to support the use of a DW.

TRUE

FALSE

154. Architects seek to design in a way that brings value to an organisation. To reach these goals, data architects define and maintain specifications that:

Align data architecture with enterprise strategy and business architecture

Provide a standard business vocabulary for data and components

Outline high-level integrated designs to meet these requirements.

Integrate with overall enterprise architecture roadmap

Define the current state of data in the organization.

Express strategic data requirements

155. A limitation of the centralized metadata repository approach is it may be less expensive.

TRUE

FALSE

156. Big data primarily refers specifically to the volume of the data.

TRUE

FALSE

157. The accuracy dimension has to do with the precision of data values.

TRUE

FALSE

158. BI tool types include:

BPM

Operational reporting

Data lake extraction

Diagnostic, self-service analytics

Descriptive, self-service analytics

Reduction of risk

159. The goals of Data Integration and Interoperability include:

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

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

Managing the availability of data throughout the data lifecycle

Provide the starting point for customizations, integration or even replacement of an application

Identify meaningful events and automatically trigger alerts and actions.

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

160. The Belmont principles that may be adapted for Information Management disciplines, include:

Respect for Persons

Respect for Machines

Beneficence

Criminality

Justice

Page 17 of 20

161. Elements that point to differences between warehouses and operational systems include:

Historical

Data security standards

Subject-orientated

Non-volatile

Data quality

Integrated

162. Please select the correct general cost and benefit categories that can be applied consistently within an organization.

Cost of erasing data from servers

Cost of improving data

What the data could be sold for

Benefit of higher quality data

Cost of replacing data if it were lost

What competitors would pay for data

163. Please select correct term for the following sentence: An organization shall assign a senior executive to appropriate individuals, adopt policies and processes to guide staff and ensure program audibility.

Principle of integrity

Principle of availability

Principle of retention

Principle of accountability

164. Please select the answers that correctly describes where the costs of poor quality data comes from.

Scrap and rework

Organizational conflict

High job satisfaction

High productivity

Reputational costs

Compliance costs

165. The implementation of a Data Warehouse should follow guiding principles, including:

Data Efficiency

One size does not fit all

Contracts

Focus on the business goals

Start with the end in mind

Collaborate

166. A ‘Golden Record’ means that it is always a 100% complete and accurate representation of all entities within the organization.

TRUE

FALSE

167. Data quality issues cannot emerge at any point in the data lifecycle.

FALSE

TRUE

168. SSD is the abbreviation for Solid State Dimension.

TRUE

FALSE

169. Please select valid modelling schemes or notations

NoSQL

Dimensional

Relational

Object-orientated

Fact-based

Matrix-based

170. Consistent input data reduces the chance of errors in associating records. Preparation processes include:

Standardization

Enrichment CValidation

Database management

Page 18 of 20

171. Confirming and documenting understanding of different perspectives facilitate:

Formalization

Normalization

Scope definition

Knowledge retention/documentation

172. The first two steps in the data science process are:

Define Big Data data strategy & Business Need(s)

Choose Data Sources

Develop Data Science Hypotheses and Mehods

Acquire & Ingest Data source(s)

173. DBAs and database architects combine their knowledge of available tools with the business requirements in order to suggest the best possible application of technology to meet organizational goals.

FALSE

TRUE

174. A synonym for transformation in ETL is mapping. Mapping is the process of developing the lookup matrix from source to target structures, but not the result of the process.

TRUE

FALSE

175. Temporal aspects usually include:

Valid time

Transmitting time

Transaction time

Value time

176. Three data governance operating models types include:

Centralized

Decentralized

Feathered

Federated

Replicated

Duplicated

177. CMA is an abbreviation for Capability Maturity Assessment.

TRUE

FALSE

178. Business people must be fully engaged in order to realize benefits from the advanced analytics.

TRUE

FALSE

179. As an often-overlooked aspects of basic data movement architecture, Process controls include:

Consistency logging

Exception logs

Database activity logs

Alerts

Exception logs

All of the above

180. There are several reasons to denormalize data. The first is to improve performance by:

Creating smaller copies of fata to reduce costly run-time calculations and/or table scans of large tables.

None of the above

Pre-calculating and sorting costly data calculations to avoid runt-time system resource competition.

Making tables more readable when no foreign key exists

Combining data from multiple other tables in advance to avoid costly run-time joins

All of the above

Page 19 of 20

181. Vulnerability is defined as:

a patch in a system that allows it to be successfully unpatched and compromised.

being highly data risk rated

a strength in a system that allows external stakeholders to view data records.

a weakness or defect in a system that allows it to be successfully attacked and compromised.

182. Data security issues, breaches and unwarranted restrictions on employee access to data cannot directly impact operational success.

TRUE

FALSE

183. Some document management systems have a module that may support different types of workflows such as:

Quality Assurance Testing (QA)

Manual workflows that indicate where the user send the document

User Acceptance Testing (UAT)

Dynamic rules that allow for different workflows based on content

All of the above

None of the above

184. Within the Data Handling Ethics Context Diagram a key deliverable is the Ethical Data Handling Strategy.

TRUE

FALSE

185. With reliable Metadata an organization does not know what data it has, what the data represents and how it moves through the systems, who has access to it, or what it means for the data to be of high quality.

TRUE

FALSE

186. The deliverables in the data architecture context diagram include:

Data flows

Enterprise data

Implementation roadmap

Data Value Chains

None of the above

All of the above

187. The primary goal of data management capability assessment is to evaluate the current state of critical data management activities in order to plan for improvement.

TRUE

FALSE

188. Master data management includes several basic steps, which include: Develop rules for accurately matching and merging entity instances.

TRUE

FALSE

189. The four main types of NoSQL databases are:

Document

Row-orientated

Graph

Strategic

Key-value

Column-orientated

190. The most common drivers for initiating a Mater Data Management Program are:

Metadata insecurity

Managing data quality

Reducing risk

Managing the costs of data integration

Meeting organizational data requirements

Reducing latency

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191. The implementation of a Data Warehouse should follow these guiding principles:

Managing performance of data assets

Focus on the business goals

Managing the availability of data throughout the data lifecycle

Start with the end in mind

Managing the performance of data transactions

Collaborate

192. Data architect: A senior analyst responsible for data architecture and data integration.

TRUE

FALSE

193. A Data Management Maturity Assessment (DMMA) can be used to evaluate data management overall, or it can be used to focus on a single Knowledge Area or even a single process.

TRUE

FALSE

194. Key processing steps for MDM include:

Data model management

Data acquisition

Data validation, standardization and enrichment

Entity resolution

Data sharing and stewardship

None of the above

195. The database administrator (DBA) is the most established and the most widely adopted data professional role.

TRUE

FALSE

196. The operational data quality management procedures depend on the ability to measure and monitor the applicability of data.

FALSE

TRUE

197. Advantages if a centralized metadata repository include:

Quick metadata retrieval

None of the above

Combining data from multiple other tables in advance to avoid costly run-time joins

All of the above

High availability

Low latency, since it is independent of the source systems

198. A goal of a Reference and Master Data Management program include enabling master and reference data to be shared across enterprise functions and applications.

FALSE

TRUE

199. Data professionals involved in Business Intelligence, analytics and Data Science are often responsible for data that describes: who people are; what people do; where people live; and how people are treated. The data can be misused and counteract the principles underlying data ethics.

FALSE

TRUE

200. Small reference data value sets in the logical data model can be implemented in a physical model in three common ways:

Create a matching separate code table

Create a master shared code table

None of the above

Program integration by joining tables

Embed rules or valid codes into the appropriate object’s definition.

Roadmap Development