McqMate
1. |
__________ is a subject-oriented, integrated, time-variant, nonvolatile collection of data in support of management decisions. |
A. | data mining. |
B. | data warehousing. |
C. | web mining. |
D. | text mining. |
Answer» B. data warehousing. |
2. |
The data Warehouse is__________. |
A. | read only. |
B. | write only. |
C. | read write only. |
D. | none. |
Answer» A. read only. |
3. |
Expansion for DSS in DW is__________. |
A. | decision support system. |
B. | decision single system. |
C. | data storable system. |
D. | data support system. |
Answer» A. decision support system. |
4. |
The important aspect of the data warehouse environment is that data found within the data warehouse is___________. |
A. | subject-oriented. |
B. | time-variant. |
C. | integrated. |
D. | all of the above. |
Answer» D. all of the above. |
5. |
The time horizon in Data warehouse is usually __________. |
A. | 1-2 years. |
B. | 3-4years. |
C. | 5-6 years. |
D. | 5-10 years. |
Answer» D. 5-10 years. |
6. |
The data is stored, retrieved & updated in ____________. |
A. | olap. |
B. | oltp. |
C. | smtp. |
D. | ftp. |
Answer» B. oltp. |
7. |
__________describes the data contained in the data warehouse. |
A. | relational data. |
B. | operational data. |
C. | metadata. |
D. | informational data. |
Answer» C. metadata. |
8. |
____________predicts future trends & behaviors, allowing business managers to make proactive, knowledge-driven decisions. |
A. | data warehouse. |
B. | data mining. |
C. | datamarts. |
D. | metadata. |
Answer» B. data mining. |
9. |
__________ is the heart of the warehouse. |
A. | data mining database servers. |
B. | data warehouse database servers. |
C. | data mart database servers. |
D. | relational data base servers. |
Answer» B. data warehouse database servers. |
10. |
________________ is the specialized data warehouse database. |
A. | oracle. |
B. | dbz. |
C. | informix. |
D. | redbrick. |
Answer» D. redbrick. |
11. |
________________defines the structure of the data held in operational databases and used by operational applications. |
A. | user-level metadata. |
B. | data warehouse metadata. |
C. | operational metadata. |
D. | data mining metadata. |
Answer» C. operational metadata. |
12. |
________________ is held in the catalog of the warehouse database system. |
A. | application level metadata. |
B. | algorithmic level metadata. |
C. | departmental level metadata. |
D. | core warehouse metadata. |
Answer» B. algorithmic level metadata. |
13. |
_________maps the core warehouse metadata to business concepts, familiar and useful to end users. |
A. | application level metadata. |
B. | user level metadata. |
C. | enduser level metadata. |
D. | core level metadata. |
Answer» A. application level metadata. |
14. |
______consists of formal definitions, such as a COBOL layout or a database schema. |
A. | classical metadata. |
B. | transformation metadata. |
C. | historical metadata. |
D. | structural metadata. |
Answer» A. classical metadata. |
15. |
_____________consists of information in the enterprise that is not in classical form. |
A. | mushy metadata. |
B. | differential metadata. |
C. | data warehouse. |
D. | data mining. |
Answer» A. mushy metadata. |
16. |
. ______________databases are owned by particular departments or business groups. |
A. | informational. |
B. | operational. |
C. | both informational and operational. |
D. | flat. |
Answer» B. operational. |
17. |
The star schema is composed of __________ fact table. |
A. | one. |
B. | two. |
C. | three. |
D. | four. |
Answer» A. one. |
18. |
The time horizon in operational environment is ___________. |
A. | 30-60 days. |
B. | 60-90 days. |
C. | 90-120 days. |
D. | 120-150 days. |
Answer» B. 60-90 days. |
19. |
The key used in operational environment may not have an element of__________. |
A. | time. |
B. | cost. |
C. | frequency. |
D. | quality. |
Answer» A. time. |
20. |
Data can be updated in _____environment. |
A. | data warehouse. |
B. | data mining. |
C. | operational. |
D. | informational. |
Answer» C. operational. |
21. |
Record cannot be updated in _____________. |
A. | oltp |
B. | files |
C. | rdbms |
D. | data warehouse |
Answer» D. data warehouse |
22. |
The source of all data warehouse data is the____________. |
A. | operational environment. |
B. | informal environment. |
C. | formal environment. |
D. | technology environment. |
Answer» A. operational environment. |
23. |
Data warehouse contains_____________data that is never found in the operational environment. |
A. | normalized. |
B. | informational. |
C. | summary. |
D. | denormalized. |
Answer» C. summary. |
24. |
The modern CASE tools belong to _______ category. |
A. | analysis. |
B. | development |
C. | coding |
D. | delivery |
Answer» A. analysis. |
25. |
Bill Inmon has estimated___________of the time required to build a data warehouse, is consumed in the conversion process. |
A. | 10 percent. |
B. | 20 percent. |
C. | 40 percent |
D. | 80 percent. |
Answer» D. 80 percent. |
26. |
Detail data in single fact table is otherwise known as__________. |
A. | monoatomic data. |
B. | diatomic data. |
C. | atomic data. |
D. | multiatomic data. |
Answer» C. atomic data. |
27. |
_______test is used in an online transactional processing environment. |
A. | mega. |
B. | micro. |
C. | macro. |
D. | acid. |
Answer» D. acid. |
28. |
___________ is a good alternative to the star schema. |
A. | star schema. |
B. | snowflake schema. |
C. | fact constellation. |
D. | star-snowflake schema. |
Answer» C. fact constellation. |
29. |
The biggest drawback of the level indicator in the classic star-schema is that it limits_________. |
A. | quantify. |
B. | qualify. |
C. | flexibility. |
D. | ability. |
Answer» C. flexibility. |
30. |
A data warehouse is _____________. |
A. | updated by end users. |
B. | contains numerous naming conventions and formats |
C. | organized around important subject areas. |
D. | contains only current data. |
Answer» C. organized around important subject areas. |
31. |
An operational system is _____________. |
A. | used to run the business in real time and is based on historical data. |
B. | used to run the business in real time and is based on current data. |
C. | used to support decision making and is based on current data. |
D. | used to support decision making and is based on historical data. |
Answer» B. used to run the business in real time and is based on current data. |
32. |
The generic two-level data warehouse architecture includes __________. |
A. | at least one data mart. |
B. | data that can extracted from numerous internal and external sources. |
C. | near real-time updates. |
D. | far real-time updates. |
Answer» B. data that can extracted from numerous internal and external sources. |
33. |
The active data warehouse architecture includes __________ |
A. | at least one data mart. |
B. | data that can extracted from numerous internal and external sources. |
C. | near real-time updates. |
D. | all of the above. |
Answer» D. all of the above. |
34. |
Reconciled data is ___________. |
A. | data stored in the various operational systems throughout the organization. |
B. | current data intended to be the single source for all decision support systems. |
C. | data stored in one operational system in the organization. |
D. | data that has been selected and formatted for end-user support applications. |
Answer» B. current data intended to be the single source for all decision support systems. |
35. |
The extract process is ______. |
A. | capturing all of the data contained in various operational systems. |
B. | capturing a subset of the data contained in various operational systems. |
C. | capturing all of the data contained in various decision support systems. |
D. | capturing a subset of the data contained in various decision support systems. |
Answer» B. capturing a subset of the data contained in various operational systems. |
36. |
Data scrubbing is _____________. |
A. | a process to reject data from the data warehouse and to create the necessary indexes. |
B. | a process to load the data in the data warehouse and to create the necessary indexes. |
C. | a process to upgrade the quality of data after it is moved into a data warehouse. |
D. | a process to upgrade the quality of data before it is moved into a data warehouse |
Answer» D. a process to upgrade the quality of data before it is moved into a data warehouse |
37. |
The load and index is ______________. |
A. | a process to reject data from the data warehouse and to create the necessary indexes. |
B. | a process to load the data in the data warehouse and to create the necessary indexes. |
C. | a process to upgrade the quality of data after it is moved into a data warehouse. |
D. | a process to upgrade the quality of data before it is moved into a data warehouse. |
Answer» B. a process to load the data in the data warehouse and to create the necessary indexes. |
38. |
Data transformation includes __________. |
A. | a process to change data from a detailed level to a summary level. |
B. | a process to change data from a summary level to a detailed level. |
C. | joining data from one source into various sources of data. |
D. | separating data from one source into various sources of data. |
Answer» A. a process to change data from a detailed level to a summary level. |
39. |
____________ is called a multifield transformation. |
A. | converting data from one field into multiple fields. |
B. | converting data from fields into field. |
C. | converting data from double fields into multiple fields. |
D. | converting data from one field to one field. |
Answer» A. converting data from one field into multiple fields. |
40. |
The type of relationship in star schema is __________________. |
A. | many-to-many. |
B. | one-to-one. |
C. | one-to-many. |
D. | many-to-one. |
Answer» C. one-to-many. |
41. |
Fact tables are ___________. |
A. | completely demoralized. |
B. | partially demoralized. |
C. | completely normalized. |
D. | partially normalized. |
Answer» C. completely normalized. |
42. |
_______________ is the goal of data mining. |
A. | to explain some observed event or condition. |
B. | to confirm that data exists. |
C. | to analyze data for expected relationships. |
D. | to create a new data warehouse. |
Answer» A. to explain some observed event or condition. |
43. |
Business Intelligence and data warehousing is used for ________. |
A. | forecasting. |
B. | data mining. |
C. | analysis of large volumes of product sales data. |
D. | all of the above. |
Answer» D. all of the above. |
44. |
The data administration subsystem helps you perform all of the following, except__________. |
A. | backups and recovery. |
B. | query optimization. |
C. | security management. |
D. | create, change, and delete information. |
Answer» D. create, change, and delete information. |
45. |
The most common source of change data in refreshing a data warehouse is _______. |
A. | queryable change data. |
B. | cooperative change data. |
C. | logged change data. |
D. | snapshot change data. |
Answer» A. queryable change data. |
46. |
________ are responsible for running queries and reports against data warehouse tables. |
A. | hardware. |
B. | software. |
C. | end users. |
D. | middle ware. |
Answer» C. end users. |
47. |
Query tool is meant for __________. |
A. | data acquisition. |
B. | information delivery. |
C. | information exchange. |
D. | communication. |
Answer» A. data acquisition. |
48. |
Classification rules are extracted from _____________. |
A. | root node. |
B. | decision tree. |
C. | siblings. |
D. | branches. |
Answer» B. decision tree. |
49. |
Dimensionality reduction reduces the data set size by removing ____________. |
A. | relevant attributes. |
B. | irrelevant attributes. |
C. | derived attributes. |
D. | composite attributes. |
Answer» B. irrelevant attributes. |
50. |
___________ is a method of incremental conceptual clustering. |
A. | corba. |
B. | olap. |
C. | cobweb. |
D. | sting. |
Answer» C. cobweb. |
51. |
Effect of one attribute value on a given class is independent of values of other attribute is called _________. |
A. | value independence. |
B. | class conditional independence. |
C. | conditional independence. |
D. | unconditional independence. |
Answer» A. value independence. |
52. |
The main organizational justification for implementing a data warehouse is to provide ______. |
A. | cheaper ways of handling transportation. |
B. | decision support. |
C. | storing large volume of data. |
D. | access to data. |
Answer» C. storing large volume of data. |
53. |
Multidimensional database is otherwise known as____________. |
A. | rdbms |
B. | dbms |
C. | extended rdbms |
D. | extended dbms |
Answer» B. dbms |
54. |
Data warehouse architecture is based on ______________. |
A. | dbms. |
B. | rdbms. |
C. | sybase. |
D. | sql server. |
Answer» B. rdbms. |
55. |
Source data from the warehouse comes from _______________. |
A. | ods. |
B. | tds. |
C. | mddb. |
D. | ordbms. |
Answer» A. ods. |
56. |
________________ is a data transformation process. |
A. | comparison. |
B. | projection. |
C. | selection. |
D. | filtering. |
Answer» D. filtering. |
57. |
The technology area associated with CRM is _______________. |
A. | specialization. |
B. | generalization. |
C. | personalization. |
D. | summarization. |
Answer» C. personalization. |
58. |
SMP stands for _______________. |
A. | symmetric multiprocessor. |
B. | symmetric multiprogramming. |
C. | symmetric metaprogramming. |
D. | symmetric microprogramming. |
Answer» A. symmetric multiprocessor. |
59. |
__________ are designed to overcome any limitations placed on the warehouse by the nature of the relational data model. |
A. | operational database. |
B. | relational database. |
C. | multidimensional database. |
D. | data repository. |
Answer» C. multidimensional database. |
60. |
MDDB stands for ___________. |
A. | multiple data doubling. |
B. | multidimensional databases. |
C. | multiple double dimension. |
D. | multi-dimension doubling. |
Answer» B. multidimensional databases. |
61. |
______________ is data about data. |
A. | metadata. |
B. | microdata. |
C. | minidata. |
D. | multidata. |
Answer» A. metadata. |
62. |
___________ is an important functional component of the metadata. |
A. | digital directory. |
B. | repository. |
C. | information directory. |
D. | data dictionary. |
Answer» C. information directory. |
63. |
EIS stands for ______________. |
A. | extended interface system. |
B. | executive interface system. |
C. | executive information system. |
D. | extendable information system. |
Answer» C. executive information system. |
64. |
___________ is data collected from natural systems. |
A. | mri scan. |
B. | ods data. |
C. | statistical data. |
D. | historical data. |
Answer» A. mri scan. |
65. |
_______________ is an example of application development environments. |
A. | visual basic. |
B. | oracle. |
C. | sybase. |
D. | sql server. |
Answer» A. visual basic. |
66. |
The term that is not associated with data cleaning process is ______. |
A. | domain consistency. |
B. | deduplication. |
C. | disambiguation. |
D. | segmentation. |
Answer» D. segmentation. |
67. |
____________ are some popular OLAP tools. |
A. | metacube, informix. |
B. | oracle express, essbase. |
C. | holap. |
D. | molap. |
Answer» A. metacube, informix. |
68. |
Capability of data mining is to build ___________ models. |
A. | retrospective. |
B. | interrogative. |
C. | predictive. |
D. | imperative. |
Answer» C. predictive. |
69. |
_____________ is a process of determining the preference of customer's majority. |
A. | association. |
B. | preferencing. |
C. | segmentation. |
D. | classification. |
Answer» B. preferencing. |
70. |
Strategic value of data mining is ______________. |
A. | cost-sensitive. |
B. | work-sensitive. |
C. | time-sensitive. |
D. | technical-sensitive. |
Answer» C. time-sensitive. |
71. |
____________ proposed the approach for data integration issues. |
A. | ralph campbell. |
B. | ralph kimball. |
C. | john raphlin. |
D. | james gosling. |
Answer» B. ralph kimball. |
72. |
The terms equality and roll up are associated with ____________. |
A. | olap. |
B. | visualization. |
C. | data mart. |
D. | decision tree. |
Answer» C. data mart. |
73. |
Exceptional reporting in data warehousing is otherwise called as __________. |
A. | exception. |
B. | alerts. |
C. | errors. |
D. | bugs. |
Answer» B. alerts. |
74. |
____________ is a metadata repository. |
A. | prism solution directory manager. |
B. | corba. |
C. | stunt. |
D. | cobweb. |
Answer» A. prism solution directory manager. |
75. |
________________ is an expensive process in building an expert system. |
A. | analysis. |
B. | study. |
C. | design. |
D. | information collection. |
Answer» D. information collection. |
76. |
The full form of KDD is _________. |
A. | knowledge database. |
B. | knowledge discovery in database. |
C. | knowledge data house. |
D. | knowledge data definition. |
Answer» B. knowledge discovery in database. |
77. |
The first International conference on KDD was held in the year _____________. |
A. | 1996. |
B. | 1997. |
C. | 1995. |
D. | 1994. |
Answer» C. 1995. |
78. |
Removing duplicate records is a process called _____________. |
A. | recovery. |
B. | data cleaning. |
C. | data cleansing. |
D. | data pruning. |
Answer» B. data cleaning. |
79. |
____________ contains information that gives users an easy-to-understand perspective of the information stored in the data warehouse. |
A. | business metadata. |
B. | technical metadata. |
C. | operational metadata. |
D. | financial metadata. |
Answer» A. business metadata. |
80. |
_______________ helps to integrate, maintain and view the contents of the data warehousing system. |
A. | business directory. |
B. | information directory. |
C. | data dictionary. |
D. | database. |
Answer» B. information directory. |
81. |
Discovery of cross-sales opportunities is called ________________. |
A. | segmentation. |
B. | visualization. |
C. | correction. |
D. | association. |
Answer» D. association. |
82. |
Data marts that incorporate data mining tools to extract sets of data are called ______. |
A. | independent data mart. |
B. | dependent data marts. |
C. | intra-entry data mart. |
D. | inter-entry data mart. |
Answer» B. dependent data marts. |
83. |
____________ can generate programs itself, enabling it to carry out new tasks. |
A. | automated system. |
B. | decision making system. |
C. | self-learning system. |
D. | productivity system. |
Answer» D. productivity system. |
84. |
The power of self-learning system lies in __________. |
A. | cost. |
B. | speed. |
C. | accuracy. |
D. | simplicity. |
Answer» C. accuracy. |
85. |
Building the informational database is done with the help of _______. |
A. | transformation or propagation tools. |
B. | transformation tools only. |
C. | propagation tools only. |
D. | extraction tools. |
Answer» A. transformation or propagation tools. |
86. |
How many components are there in a data warehouse? |
A. | two. |
B. | three. |
C. | four. |
D. | five. |
Answer» D. five. |
87. |
Which of the following is not a component of a data warehouse? |
A. | metadata. |
B. | current detail data. |
C. | lightly summarized data. |
D. | component key. |
Answer» D. component key. |
88. |
________ is data that is distilled from the low level of detail found at the current detailed leve. |
A. | highly summarized data. |
B. | lightly summarized data. |
C. | metadata. |
D. | older detail data. |
Answer» B. lightly summarized data. |
89. |
Highly summarized data is _______. |
A. | compact and easily accessible. |
B. | compact and expensive. |
C. | compact and hardly accessible. |
D. | compact. |
Answer» A. compact and easily accessible. |
90. |
A directory to help the DSS analyst locate the contents of the data warehouse is seen in ______. |
A. | current detail data. |
B. | lightly summarized data. |
C. | metadata. |
D. | older detail data. |
Answer» C. metadata. |
91. |
Metadata contains atleast _________. |
A. | the structure of the data. |
B. | the algorithms used for summarization. |
C. | the mapping from the operational environment to the data warehouse. |
D. | all of the above. |
Answer» D. all of the above. |
92. |
Which of the following is not a old detail storage medium? |
A. | phot optical storage. |
B. | raid. |
C. | microfinche. |
D. | pen drive. |
Answer» D. pen drive. |
93. |
The data from the operational environment enter _______ of data warehouse. |
A. | current detail data. |
B. | older detail data. |
C. | lightly summarized data. |
D. | highly summarized data. |
Answer» A. current detail data. |
94. |
The data in current detail level resides till ________ event occurs. |
A. | purge. |
B. | summarization. |
C. | archieved. |
D. | all of the above. |
Answer» D. all of the above. |
95. |
The dimension tables describe the _________. |
A. | entities. |
B. | facts. |
C. | keys. |
D. | units of measures. |
Answer» B. facts. |
96. |
The granularity of the fact is the _____ of detail at which it is recorded. |
A. | transformation. |
B. | summarization. |
C. | level. |
D. | transformation and summarization. |
Answer» C. level. |
97. |
Which of the following is not a primary grain in analytical modeling? |
A. | transaction. |
B. | periodic snapshot. |
C. | accumulating snapshot. |
D. | all of the above. |
Answer» B. periodic snapshot. |
98. |
Granularity is determined by ______. |
A. | number of parts to a key. |
B. | granularity of those parts. |
C. | both a and b. |
D. | none of the above. |
Answer» C. both a and b. |
99. |
___________ of data means that the attributes within a given entity are fully dependent on the entire primary key of the entity. |
A. | additivity. |
B. | granularity. |
C. | functional dependency. |
D. | dimensionality. |
Answer» C. functional dependency. |
100. |
A fact is said to be fully additive if ___________. |
A. | it is additive over every dimension of its dimensionality. |
B. | additive over atleast one but not all of the dimensions. |
C. | not additive over any dimension. |
D. | none of the above. |
Answer» A. it is additive over every dimension of its dimensionality. |
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