For courses on Business Intelligence or Decision Support Systems.
A managerial approach to understanding business intelligence systems.
To help future managers use and understand analytics, Business Intelligence provides students with a solid foundation of BI that is reinforced with hands-on practice.
本書特色
For courses on Business Intelligence or Decision Support Systems.
A managerial approach to understanding business intelligence systems.
To help future managers use and understand analytics, Business Intelligence provides students with a solid foundation of BI that is reinforced with hands-on practice.
See the decision-making aspects: Managerial Approach. This text takes a managerial approach to Business Intelligence (BI), emphasizing the applications and implementations behind the
concepts. This approach allows students to understand how BI works in a way that will help them adopt these technologies in future managerial roles.
Put the concepts into action: Access to the Teradata Network. Teradata University Network (TUN) is a free learning portal sponsored by Teradata, a division of NCR, whose objective is to help
faculty learn, teach, communicate, and collaborate with others in the field of BI. Teradata also supports a student portal (teradatastudentnetwork.com) that contains a variety of learning
resources such as cases, Web seminars, tutorials, exercises, links to sources, and more. Business Intelligence is interconnected with TUN via various hands-on assignments provided in all
chapters and is accessible to students through the portal.
Understand the context: Real-world Orientation. Extensive, vivid examples from large corporations, small businesses, and government and not-for-profit agencies make the difficult concepts
more accessible and relevant. International examples of global competition, partnerships, and trade are also provided throughout. These real-world case studies show students the capabilities of
BI, its cost and justification, and the innovative ways real corporations are using BI in their operations.
Opening Vignette: Real world case that presents a challenge, solution, and results that introduce the chapter. Each opening vignette is paired with questions for students to dig into the
details and think critically about the case.
Application Cases: Real world cases that emphasize concepts in the chapter, paired with discussion questions.
Section Review Questions: Checkpoints for students on key concepts they should have learned in the section.
Color charts, graphs, and figures: Help students visualize data, processes, and stay engaged with the content.
Technology Insights: Boxed features focusing on the benefits of available technology.
Resources, Links, and the Teradata University: Appear at the end of chapter and provide students additional reading, information, and cases to explore.
End of Chapter: Includes a list of Chapter Highlights, Key Terms, Discussion Questions, Exercises, and an additional Application Case to help students review, test, and apply their
understanding.
目錄
Ch1: An Overview of Business Intelligence, Analytics, and Data Science
Ch2: Descriptive Analytics I: Nature of Data, Statistical Modeling, and Visualization
Ch3: Descriptive Analytics II: Business Intelligence and Data Warehousing
Ch4: Predictive Analytics I: Data Mining Process, Methods, and Algorithms
Ch5: Predictive Analytics II: Text, Web, and Social Media
Ch6: Prescriptive Analytics: Optimization and Simulation
Ch7: Big Data Concepts and Tools
Ch8: Future Trends, Privacy and Managerial Considerations in Analytics
Ch2: Descriptive Analytics I: Nature of Data, Statistical Modeling, and Visualization
Ch3: Descriptive Analytics II: Business Intelligence and Data Warehousing
Ch4: Predictive Analytics I: Data Mining Process, Methods, and Algorithms
Ch5: Predictive Analytics II: Text, Web, and Social Media
Ch6: Prescriptive Analytics: Optimization and Simulation
Ch7: Big Data Concepts and Tools
Ch8: Future Trends, Privacy and Managerial Considerations in Analytics
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