Business Analytics Value Chain : Text and Cases

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Business Analytics Value Chain : Text and Cases

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  • 製本 Hardcover:ハードカバー版/ページ数 510 p.
  • 言語 ENG
  • 商品コード 9781032598116
  • DDC分類 658.4032

Full Description

This book is a comprehensive, step-by-step learning guide towards understanding an entire value chain of Business Analytics, its interrelated components and its role in business decision-making in India and globally. The book has been written with an interdisciplinary approach that triggers strategic as well as routine, thought-provoking ideas to cut across data from several business domains globally.

Business Analytics Value Chain deals with the end-to-end journey from planning the approach to a data enriched decision-problem, to communicating results derived from analytics models to clients. Using current cases from all aspects of a business venture (finance, marketing, human resources, and operations), the book helps the readers to develop the capabilities of evaluating a business case scenario; understand the business problem; identify the data sources and data availability; logically think through problemsolving; use analytics techniques and application software to solve the problem; and be able to interpret the results. Case studies have been carefully designed to represent business scenarios from varied business domains, both local and global, such that they guide the students to making informed fact-based decisions during collaborative planning, analyzing, interpreting, and communicating outcomes for data-enriched problem scenarios.

The book will be useful for students, researchers, and instructors from the fields of Business Management, Data Analytics, Commerce, and Economics. It will also be an indispensable companion to the professional working in the field of data analytics.

Contents

SECTION I: PLANNING 1. Introduction to Business Analytics. 2. Data Analytics for Business. 3. Data Exploration in Business Analytics. 4. Mapping Chart for Analytics Outcome. 5. Technology Infrastructure for Business Analytics. SECTION II: PROCESSING 6. Inferential Statistics: Preparing to be a Data Scientist. 7. Analytical Methods for Parametric and Non-Parametric Data 8. Analytical Methods for Complex Data.9. Data Mining/ Machine Learning for Business Analytics. SECTION III: COMMUNICATING 10. Interpreting the Statistical Outcomes. 11. Documenting the Process. 12. Building the Storyboard of Outcomes. APPENDIX Appendix A: Case - Trasha Beverages Goes the Business Analytics Way Appendix B: Business Case - Using Analytics for Business Problem-solving Appendix C: Online Grocery Case Appendix D: Tips on Using Software Used in This Book.

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