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Test Bank for Business Intelligence 4th Edition by Sharda, Delen and Turban A+
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Test Bank For Business Intelligence, Analytics, and Data Science: A Managerial Perspective 4th Edition by Sharda; Delen & Turban, ISBN: 9780134633282, All 8 Chapters Covered, Verified Latest Edition
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Test Bank For Business Intelligence, Analytics, and Data Science: A Managerial Perspective 4th Edition by Sharda; Delen & Turban, ISBN: 9780134633282, All 8 Chapters Covered, Verified Latest Edition
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Test Bank For Business Intelligence, Analytics, and Data Science: A Managerial Perspective 4th Edition by Sharda; Delen & Turban All 1-8 Chapters Covered ,Latest Edition, ISBN:9780134633282
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Voorbeeld van de inhoud
Created By: A SolutionTest Bank for Business Intelligence 4th Edition by Sharda,
Delen and Turban A+
Chapter 1: An Overview of Business Intelligence, Analytics, and Data Science
1) Computerized support is only used for organizational decisions that are responses to
external pressures, not for taking advantage of opportunities.
Answer: FALSE Diff: 2 Page Ref: 3
2) During the early days of analytics, data was often obtained from the domain experts using
manual processes to build mathematical or knowledge-based models.
Answer: TRUE
Diff: 2 Page Ref: 13
3) Computer applications have moved from transaction processing and monitoring activities
to problem analysis and solution applications.
Answer: TRUE
Diff: 1 Page Ref: 11
4) Business intelligence (BI) is a specific term that describes architectures and tools only.
Answer: FALSE
Diff: 1 Page Ref: 16
1
,Created By: A Solution
5) The growth in hardware, software, and network capacities has had little impact on
modern BI innovations.
Answer: FALSE
Diff: 1 Page Ref: 11
6) Managing data warehouses requires special methods, including parallel computing and/or
Hadoop/Spark.
Answer: TRUE
Diff: 3 Page Ref: 11-12
7) Managing information on operations, customers, internal procedures and employee
interactions is the domain of cognitive science.
Answer: FALSE
Diff: 3 Page Ref: 12
8) Decision support system (DSS) and management information system (MIS) have precise
definitions agreed to by practitioners.
Answer: FALSE
Diff: 2 Page Ref: 13
9) In the 2000s, the DW-driven DSSs began to be called BI systems. Answer: TRUE
Diff: 1 Page Ref: 14
2
,Created By: A Solution
10) Major commercial business intelligence (BI) products and services were well established
in the early 1970s.
Answer: FALSE
Diff: 2 Page Ref: 15
11) Information systems that support such transactions as ATM withdrawals, bank deposits,
and cash register scans at the grocery store represent transaction processing, a critical branch of
BI. Answer: FALSE
Diff: 2 Page Ref: 19
12) Many business users in the 1980s referred to their mainframes as "the black hole,"
because all the information went into it, but little ever came back and ad hoc real-time querying
was virtually impossible.
Answer: TRUE
Diff: 2 Page Ref: 20
13) Successful BI is a tool for the information systems department, but is not exposed to the
larger organization.
Answer: FALSE
Diff: 2 Page Ref: 20
14) BI represents a bold new paradigm in which the company's business strategy must be
aligned to its business intelligence analysis initiatives.
Answer: FALSE
3
, Created By: A Solution
Diff: 2 Page Ref: 20-21
15) Traditional BI systems use a large volume of static data that has been extracted, cleansed,
and loaded into a data warehouse to produce reports and analyses.
Answer: TRUE
Diff: 2 Page Ref: 21
16) Demands for instant, on-demand access to dispersed information decrease as firms
successfully integrate BI into their operations.
Answer: FALSE
Diff: 3 Page Ref: 21
17) The use of dashboards and data visualizations is seldom effective in identifying issues in
organizations, as demonstrated by the Silvaris Corporation Case Study.
Answer: FALSE
Diff: 2 Page Ref: 24
18) The use of statistics in baseball by the Oakland Athletics, as described in the Moneyball
case study, is an example of the effectiveness of prescriptive analytics.
Answer: TRUE
Diff: 2 Page Ref: 5
19) Due to industry consolidation, the analytics ecosystem consists of only a handful of
players across several functional areas.
4
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