Data Management Fundamentals DMF-1220 Practice Test Questions (486 Q&As)

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

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

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.

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

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

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

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.

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

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

10. SLA Stands for:

11. Different types of product Master Data solutions include:

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

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

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

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

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

17. Most document programs have policies related to:

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

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

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.

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

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.

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

24. All metadata management solutions include architectural layers including:

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

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

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

28. Some ways to measure value of data include:

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

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

31. Data profiling examples include:

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

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

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

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

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

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

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

40. The Shewhart chart contains the following elements:

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

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

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

44. Examples of technical metadata include:

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.

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

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

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

49. Please select the correct General Accepted Information Principles:

50. Corporate Information Factory (CIF) components include:

51. Inputs in the data quality context diagram include:

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

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

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:

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

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

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

58. BI tool types include:

59. The goals of Data Integration and Interoperability include:

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

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

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

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.

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

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

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

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

68. SSD is the abbreviation for Solid State Dimension.

69. Please select valid modelling schemes or notations

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

71. Confirming and documenting understanding of different perspectives facilitate:

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

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.

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.

75. Temporal aspects usually include:

76. Three data governance operating models types include:

77. CMA is an abbreviation for Capability Maturity Assessment.

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

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

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

81. Vulnerability is defined as:

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

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

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

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.

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

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.

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

89. The four main types of NoSQL databases are:

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

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

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

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.

94. Key processing steps for MDM include:

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

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

97. Advantages if a centralized metadata repository include:

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.

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.

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

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

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

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.

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

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

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

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.

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

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

110. SLA Stands for:

111. Different types of product Master Data solutions include:

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

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

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

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

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

117. Most document programs have policies related to:

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

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

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.

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

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.

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

124. All metadata management solutions include architectural layers including:

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

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

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

128. Some ways to measure value of data include:

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

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

131. Data profiling examples include:

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

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

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

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

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

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

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

140. The Shewhart chart contains the following elements:

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

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

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

144. Examples of technical metadata include:

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.

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

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

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

149. Please select the correct General Accepted Information Principles:

150. Corporate Information Factory (CIF) components include:

151. Inputs in the data quality context diagram include:

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

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

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:

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

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

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

158. BI tool types include:

159. The goals of Data Integration and Interoperability include:

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

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

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

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.

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

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

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

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

168. SSD is the abbreviation for Solid State Dimension.

169. Please select valid modelling schemes or notations

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

171. Confirming and documenting understanding of different perspectives facilitate:

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

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.

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.

175. Temporal aspects usually include:

176. Three data governance operating models types include:

177. CMA is an abbreviation for Capability Maturity Assessment.

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

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

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

181. Vulnerability is defined as:

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

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

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

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.

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

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.

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

189. The four main types of NoSQL databases are:

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

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

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

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.

194. Key processing steps for MDM include:

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

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

197. Advantages if a centralized metadata repository include:

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.

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.

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