Business analytics: text and cases

By: Banerjee, Tanushri
Contributor(s): Banerjee, Arindam [Co-author]
Material type: TextTextPublisher: New Delhi Sage Publications India 2019Description: xxvi, 332 p.: ill. Includes references and indexISBN: 9789353287108Subject(s): Business productivity | Business analytics - Technology infrastructure | Data mining techniques | Mapping chart - Analysis outcomeDDC classification: FP 658.4038 Summary: This textbook is a comprehensive, step-by-step learning guide to each aspect of business analytics and its role and significance in real-life business decision-making. Correct capture, analysis, and interpretation of data can have an immense impact on business productivity. Therefore, business analytics has turned out to be a strategic need for sustainability and growth in this competitive world. Descriptive, predictive, and prescriptive models and data mining techniques are increasingly being used to interpret large quantities of data for getting useful business insights. Business Analytics: Text and Cases deal with the end-to-end journey from planning the approach to a data-enriched decision-problem, to communicating the results derived from analytics models to clients. Using cases from all aspects of a business venture (finance, marketing, human resource, and operations), the book helps students to develop the skill to evaluate a business case scenario, understand the business problems, identify the data sources and data availability, logically think through problem-solving, use analytics techniques and application software to solve the problem and be able to interpret the results. Key Features: •Case studies of three degrees of difficulty level to enhance better understanding of the concepts •Application of software tools such as Microsoft Excel, R, SPSS, RapidMiner and Tableau to assist learning in building models and communicating results using analytics, data mining and data visualization •End of book Appendix consisting of step-by-step solved comprehensive case studies that discuss the concepts of all the chapters •Special emphasis on the need to develop the skill for interpreting the outcome from the statistical results and presenting it in a form easily understood by the end-user/client https://in.sagepub.com/en-in/sas/business-analytics/book271732
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Books Vikram Sarabhai Library
Faculty Publication
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Table of contents

Foreword by Dr. Suresh Divakar
Preface
Acknowledgments
Introduction to Business Analytics
Data Analytics for Business
Data Exploration in Business Analytics
Mapping Chart for Analytics Outcomes
Technology Infrastructure for Business Analytics
Analytical Methods for Parametric and Non-parametric Data
Analytical Methods for Complex Data
Data Mining Methods in Business Analytics
Interpreting the Statistical Outcomes
Documenting the Processes
Building the Storyboard of Outcomes
Appendices
Index

This textbook is a comprehensive, step-by-step learning guide to each aspect of business analytics and its role and significance in real-life business decision-making.
Correct capture, analysis, and interpretation of data can have an immense impact on business productivity. Therefore, business analytics has turned out to be a strategic need for sustainability and growth in this competitive world. Descriptive, predictive, and prescriptive models and data mining techniques are increasingly being used to interpret large quantities of data for getting useful business insights.
Business Analytics: Text and Cases deal with the end-to-end journey from planning the approach to a data-enriched decision-problem, to communicating the results derived from analytics models to clients. Using cases from all aspects of a business venture (finance, marketing, human resource, and operations), the book helps students to develop the skill to evaluate a business case scenario, understand the business problems, identify the data sources and data availability, logically think through problem-solving, use analytics techniques and application software to solve the problem and be able to interpret the results.
Key Features:
•Case studies of three degrees of difficulty level to enhance better understanding of the concepts
•Application of software tools such as Microsoft Excel, R, SPSS, RapidMiner and Tableau to assist learning in building models and communicating results using analytics, data mining and data visualization
•End of book Appendix consisting of step-by-step solved comprehensive case studies that discuss the concepts of all the chapters
•Special emphasis on the need to develop the skill for interpreting the outcome from the statistical results and presenting it in a form easily understood by the end-user/client

https://in.sagepub.com/en-in/sas/business-analytics/book271732

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