Business Intelligence, Analytics, and Data Science: A Managerial Perspective
Ramesh Sharda
4th Edition
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,Table of Contents
1. An Overview of Business Intelligence, Analytics, and Data Science
2. Descriptive Analytics I: Nature of Data, Statistical Modeling, and Visualization
3. Descriptive Analytics II: Business Intelligence and Data Warehousing
4. Predictive Analytics I: Data Mining Process, Methods, and Algorithms
5. Predictive Analytics II: Text, Web, and Social Media Analytics
6. Prescriptive Analytics: Optimization and Simulation
7. Big Data Concepts and Tools
8. Future Trends, Privacy and Managerial Considerations in Analytics
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Chapter01: 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
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Diff: 2 Page Ref: 13
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3) Computer applications have moved from transaction processing and monitoring activities
to problem analysis and solution applications.
ANSWER- TRUE
Diff: 1 Page Ref: 11
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4) Business intelligence (BI) is a specific term that describes architectures and tools only.
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ANSWER- FALSE
Diff: 1 Page Ref: 16
5) The growth in hardware, software, and network capacities has had little impact on
modern BI innovations.
ANSWER- FALSE
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Diff: 1 Page Ref: 11
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6) Managing data warehouses requires special methods, including parallel computing and/or
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Hadoop/Spark.
ANSWER- TRUE
Diff: 3 Page Ref: 11-12
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7) Managing information on operations, customers, internal procedures and employee
interactions is the domain of cognitive science.
ANSWER- FALSE
Diff: 3 Page Ref: 12