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Test Bank for Business Intelligence, Analytics, Data Science, and AI – 5th Edition by Ramesh Sharda, Dursun Delen, Efraim Turban – Full Pack Test Bank with Solutions (Ch. 1–11) || Latest 2025/2026 || Instant Download

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The Test Bank for Business Intelligence, Analytics, Data Science, and Artificial Intelligence, 5th Edition by Ramesh Sharda, Dursun Delen, and Efraim Turban is the complete resource for mastering today’s most advanced topics in business analytics and AI-driven decision-making. This latest 2025/2026 edition provides chapter-by-chapter test items and solutions (Chapters 1–11 fully covered). It is designed to support both instructors and students with multiple-choice questions, true/false, short-answer, and application-based problems, all verified for accuracy and updated to reflect modern business intelligence trends. Key topics include: Foundations of Business Intelligence & Analytics Data Warehousing and Data Mining Big Data Analytics and Emerging Technologies Artificial Intelligence and Machine Learning in Business Data Visualization and Storytelling with Analytics Predictive Analytics, Prescriptive Analytics, and Simulation Ethical and Managerial Issues in AI & Analytics Applications of BI in Strategic Decision-Making All 11 chapters included – complete coverage. Verified A+ solutions – accuracy guaranteed. Instant download – no waiting, immediate access. Ideal for exam prep, quizzes, assignments, and self-study. This test bank equips learners with the tools to practice, test their understanding, and achieve higher grades in business analytics and AI courses. Instructors can rely on it to design high-quality assessments, while students benefit from realistic practice questions that mirror actual exam formats.

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Test Bank For Business Intelligence, Analytics,
Data Science, and AI, 5th Edition by Ramesh
Sharda, Dursun Delen, Efraim Turban Chapter
1-11 All Included Latest Update

Contents
Chapter 1 An Overview of Business Intelligence, Analytics, and Data Science.............................................2
Chapter 2 Artificial Intelligence: Concepts, Drivers, Major Technologies, and Business Applications........30
Chapter 3 Descriptive Analytics I: Nature of Data, Big Data, and Statistical Modeling...............................59
Chapter 4 Descriptive Analytics II: Business Intelligence Data Warehousing, and Visualization................91
Chapter 5 Predictive Analytics I: Data Mining Process, Methods, and Algorithms...................................123
Chapter 6 Predictive Analytics II: Text, Web, and Social Media Analytics................................................155
Chapter 7 Deep Learning and Cognitive Computing................................................................................185
Chapter 8 Prescriptive Analytics: Optimization and Simulation...............................................................215
Chapter 9 The Landscape of Software Tools and Languages....................................................................247
Chapter 10 New AI-Based Trends in Analytics and Data Science.............................................................278
Chapter 11 Ethical, Privacy and Managerial Considerations in Analytics.................................................311




1
Copyright © 2024 Pearson Education Ltd.

,Chapter 1 An Overview of Business Intelligence,
Analytics, and Data Science

1) Computerized support is used for organizational and managerial decisions that
are responses to external pressures and to take advantage of market opportunities.
Answer: TRUE
Diff: 1 Page Ref: 32


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: 56


3) Computer applications have moved from transaction processing and monitoring
activities to problem analysis and decision support applications.
Answer: TRUE
Diff: 1 Page Ref: 48


4) Business intelligence is a specific term that describes a variety of information
technology and data capturing focused system architectures.
Answer: FALSE
Diff: 2 Page Ref: 46


5) The growth in hardware, software, and network capacities were the core
contributors to the proliferation of decision support and analytics systems.
Answer: FALSE
Diff: 2 Page Ref: 48

2
Copyright © 2024 Pearson Education Ltd.

,6) Managing data warehouses requires special methods, including parallel and
cloud computing along with Hadoop/Spark.
Answer: TRUE
Diff: 2 Page Ref: 49


7) Managing information on operations, customers, internal procedures, and
employee interactions is the domain of cognitive science.
Answer: FALSE
Diff: 3 Page Ref: 49


8) Decision support system (DSS), analytics, and management information system
(MIS) have precise definitions agreed to by most practitioners.
Answer: FALSE
Diff: 2 Page Ref: 55


9) Of all analytics types (i.e., descriptive, predictive, and prescriptive), data mining
is most closely related to predictive analytics.
Answer: TRUE
Diff: 1 Page Ref: 65
10) Major commercial business intelligence (BI) products and services were well
established in the early 1970s.
Answer: FALSE
Diff: 2 Page Ref: 55


11) Information systems that support such transactions as ATM withdrawals, bank
deposits, and cash register scans at the grocery store represent online transaction

3
Copyright © 2024 Pearson Education Ltd.

, processing systems (OLAP).
Answer: FALSE
Diff: 3 Page Ref: 61


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: 61


13) Data warehouses are intended to work with informational data used for online
transaction processing (OLTP) systems.
Answer: TRUE
Diff: 2 Page Ref: 61


14) Successful BI is a tool developed by and developed for the information
systems department.
Answer: FALSE
Diff: 2 Page Ref: 61


15) The time between new paradigm shifts in information systems and particularly
in analytics has been getting longer.
Answer: FALSE
Diff: 2 Page Ref: 57


16) 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

4
Copyright © 2024 Pearson Education Ltd.
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