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Test Bank for Business Intelligence, Analytics, Data Science, and AI – 5th Edition (Ramesh Sharda) | All Chapters 1-11 | ISBN 9780137931286 | Data Analytics & AI Exam Prep 2026/2027

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Test Bank for Business Intelligence, Analytics, Data Science, and AI, 5th Edition by Ramesh Sharda, Dursun Delen & Efraim Turban — complete question-and-answer bank containing 3,200+ meticulously crafted questions covering all 11 chapters across 5 parts. The gold standard textbook in BI, Data Analytics, Data Science, and AI — the 5th edition expands coverage to include Generative AI, Ethical AI Governance, AutoML Platforms, Explainable AI (XAI), and Edge Analytics — topics now central to Fortune 500 strategies and startup innovation. 3,200+ Questions — Multiple-Choice, True/False, Short-Answer, Essay & Critical-Thinking Scenarios Print ISBN-13: 9780137931286 | eBook ISBN-13: 9780137931354 | Publisher: Pearson Education | Copyright © 2024 | All 11 Chapters Complete What's included: PART I – FOUNDATIONS & AI OVERVIEW Chapter 1 – An Overview of Business Intelligence, Analytics, Data Science, and AI NEW: Generative AI overview Chapter 2 – Artificial Intelligence: Concepts, Drivers, Major Technologies & Business Applications NEW: ChatGPT, Large Language Models, Generative AI PART II – DESCRIPTIVE & PREDICTIVE ANALYTICS Chapter 3 – Descriptive Analytics I: Nature of Data, Big Data & Statistical Modeling Chapter 4 – Descriptive Analytics II: Business Intelligence, Data Warehousing & Visualization Data visualization, dashboards, BI tools Chapter 5 – Predictive Analytics I: Data Mining Process, Methods & Algorithms Classification, clustering, regression Chapter 6 – Predictive Analytics II: Text, Web & Social Media Analytics NLP, sentiment analysis, text mining PART III – ADVANCED ANALYTICS & MACHINE LEARNING Chapter 7 – Deep Learning and Cognitive Computing Neural networks, CNN, RNN, transformers, LLMs Chapter 8 – Prescriptive Analytics: Optimization and Simulation Decision support systems, simulation PART IV – AI TOOLS & IMPLEMENTATION Chapter 9 – Landscape of Business Analytics Tools Python, R, Tableau, Power BI, AutoML platforms Chapter 10 – AI-Based Trends in Analytics and Data Science Edge analytics, IoT, AI-augmented decision-making PART V – RESPONSIBLE AI & GOVERNANCE Chapter 11 – Ethical, Privacy & Managerial Considerations in Analytics Explainable AI (XAI), responsible AI, data privacy, GDPR Why this test bank? 3,200+ Questions — the most comprehensive question bank for this title; multiple-choice, true/false, short-answer, essay & critical-thinking scenarios All 11 chapters — fully aligned to 5th edition with coverage of Generative AI, Machine Learning, AutoML, XAI & Responsible AI Bloom's Taxonomy tagging — every question tagged by cognitive level (Remember/Understand/Apply/Analyze/Evaluate/Create) for progressive learning Updated 2024 content — reflects latest industry trends: GPT-4, Claude, generative AI, ethical AI governance, synthetic data generation Covers Business Intelligence fundamentals, descriptive/predictive/prescriptive analytics, deep learning, NLP, computer vision, data visualization, data warehousing, optimization, simulation & decision support Written by Ramesh Sharda (Oklahoma State University), Dursun Delen (Oklahoma State University) & Efraim Turban (University of Hawaii) — three of the world's most cited data science & business intelligence researchers Perfect for MIS, data science, business analytics, computer science & engineering students Ideal prep for data science bootcamps, internships, job interviews & professional certifications (Google Cloud, AWS, Azure Data Scientist) Compatible with Pearson Pearson+ digital learning platforms 2 ISBN variants — works for print and eBook formats Instant digital download — study anywhere, anytime Whether you're preparing for business intelligence exams, mastering data science and machine learning concepts, preparing for data scientist job interviews, or studying AI-driven decision-making for professional advancement, this complete Sharda, Delen & Turban test bank gives you everything you need. Trusted by data science and business analytics students and professionals worldwide. Download now — instant access after purchase!

Meer zien Lees minder
Instelling
Management Information Systems
Vak
Management Information Systems

Voorbeeld van de inhoud

Business Intelligence, Analytics, Data Science, and AI, 5e (Sharda)
Chapter 1 An Overview of Business Intelligence, Analytics, and Data Science

1) Computerized support is used for organizational and managerial decisions that are responses
tu
to external pressures and to take advantage of market opportunities.
Answer: TRUE
Diff: 1 Page Ref: 2
d
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.
yg
Answer: TRUE
Diff: 2 Page Ref: 26

3) Computer applications have moved from transaction processing and monitoring activities to
problem analysis and decision support applications.
en
Answer: TRUE
Diff: 1 Page Ref: 18

4) Business intelligence is a specific term that describes a variety of information technology and
data capturing focused system architectures.
iu
Answer: FALSE
Diff: 2 Page Ref: 16
s2
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: 18
47
6) Managing data warehouses requires special methods, including parallel and cloud computing
along with Hadoop/Spark.
Answer: TRUE
Diff: 2 Page Ref: 19
??
7) Managing information on operations, customers, internal procedures, and employee
interactions is the domain of cognitive science.
Answer: FALSE
??
Diff: 3 Page Ref: 19

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: 25

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: 35
?
1
Copyright © 2024 Pearson Education, Inc.

, 10) Major commercial business intelligence (BI) products and services were well established in
the early 1970s.
Answer: FALSE
Diff: 2 Page Ref: 25
tu
11) Information systems that support such transactions as ATM withdrawals, bank deposits, and
cash register scans at the grocery store represent online transaction processing systems (OLAP).
Answer: FALSE
d
Diff: 3 Page Ref: 31
yg
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: 31
en
13) Data warehouses are intended to work with informational data used for online transaction
processing (OLTP) systems.
Answer: TRUE
Diff: 2 Page Ref: 31
iu
14) Successful BI is a tool developed by and developed for the information systems department.
Answer: FALSE
s2
Diff: 2 Page Ref: 31

15) The time between new paradigm shifts in information systems and particularly in analytics
has been getting longer.
47
Answer: FALSE
Diff: 2 Page Ref: 27

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 analyses.
??
Answer: TRUE
Diff: 2 Page Ref: 32

17) 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

18) Simon's decision process involves three major phases: intelligence, design, and choice.
??
Answer: TRUE
Diff: 1 Page Ref: 20
? ?
2
Copyright © 2024 Pearson Education, Inc.

, 19) The use of dashboards and data visualizations is often very effective in identifying issues and
opportunities in organizations.
Answer: TRUE
Diff: 2 Page Ref: 36
tu
20) The use of statistics in baseball by the Oakland Athletics, as described in the Moneyball case
study, is an example of the effectiveness of data analytics.
Answer: TRUE
d
Diff: 2 Page Ref: 3
yg
21) The intelligence phase of the decision process involves developing a model that represents
the underlying system.
Answer: FALSE
Diff: 2 Page Ref: 20
en
22) The goal of prescriptive analytics is to use data and machine learning tools to forecast the
future values of the variables of interest.
Answer: FALSE
Diff: 2 Page Ref: 36
iu
23) Descriptive analytics is often called reporting analytics with the goal of answering the
question of "what happened."
Answer: FALSE
s2
Diff: 1 Page Ref: 42

24) In the design phase of the human decision process, the problem or opportunity is defined
based on all available data and information.
47
Answer: FALSE
Diff: 2 Page Ref: 21

25) Business analytics continuum starts with predictive analytics, continues with descriptive
analytics and ends with prescriptive analytics.
??
Answer: FALSE
Diff: 2 Page Ref: 25

26) In the Opening Vignette on Sports Analytics, what was adjusted to drive one-time ticket
??
sales?
A) Player selections
B) Stadium location
C) Fan tweets
D) Ticket prices
??
Answer: D
Diff: 2 Page Ref: 5
? ?
3
Copyright © 2024 Pearson Education, Inc.

, 27) In the Opening Vignette on Sports Analytics, what type of modeling was used to predict
offensive tactics?
A) Heuristics
B) Heat maps
tu
C) Cascaded decision trees
D) Sentiment analysis
Answer: B
Diff: 3 Page Ref: 8-10
d
28) Computer applications have moved from transaction processing and monitoring to other
yg
activities. Which of the following is not one of those activities?
A) Problem analysis
B) Solution applications
C) Data monitoring
D) Cloud-based technologies
en
Answer: C
Diff: 3 Page Ref: 18

29) Which of the following developments is not contributing to facilitating growth of decision
support and analytics?
iu
A) Collaboration technologies
B) Data management
C) Knowledge management
s2
D) Locally concentrated workforces
Answer: D
Diff: 3 Page Ref: 18-19
47
30) In what decade did separate information systems within the organizations begin to be
integrated?
A) 1970s
B) 1980s
C) 1990s
??
D) 2000s
Answer: B
Diff: 2 Page Ref: 25
??
31) Relational databases began to be used in which of the following time windows?
A) 1960s
B) 1970s
C) 1980s
D) 1990s
??
Answer: C
Diff: 3 Page Ref: 25-26
? ?
4
Copyright © 2024 Pearson Education, Inc.

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