Authors:
Nitin Kalé, Univ. of Southern California & Nancy Jones, San Diego State Univ.
Ordering Information: Kalé, Nitin and Jones, Nancy. “Practical Analytics, 2nd Ed” 2020
ISBN: 9780997209242
Order Site: http://store.epistemypress.com/books/analytics.html
Overview: Practical Analytics, 2nd ed. explains analytics concepts and activities in a way that provides real-world skill building while reinforcing fundamental concepts. This book provides a much needed approach to analytics through theory, applications, and hands-on experience using the latest industry tools. Although many books have been written on statistical data analysis, data mining, predictive analytics and business intelligence, these books are often too technical for a business user. The goal of this book is to provide a comprehensive and self-contained overview of analytics concepts and practical experience executing those concepts with market-leading enterprise software solutions. The reader will be able to learn and apply all the concepts in the book without excessive prerequisite knowledge or experience.
Audience: This book is intended for business users who are increasingly required to use analytical tools to perform their job responsibilities and university students who are interested in a career as a data analyst or business user/executive.
Course/Experience Prerequisites:
- An introductory course in information technology covering information systems, internet, technology enabled business, spreadsheets, databases, digital representation of data, basics of hardware and software, and business processes -or ~3 years of industry experience as a user of enterprise systems
- Basic skills in Microsoft Excel – working with tables, formulae, sorting, filtering and charting
- Introductory course on statistics
Suggested Course Duration: The book is designed to be the basis for a 15 week long semester covering 45 contact hours. Each chapter would be covered in approximately one 3 hour lecture followed by take home/lab assignments. These assignments include exercises and projects using SAP and other common Analytics applications. Students are expected to spend between 2-4 hours a week on the assignments. Sample syllabi for various courses will be available on the textbook website. Section 2 is intended for a more technical audience. It can be bypassed in a purely business oriented class. Such a class can spend more time on case studies in the remaining 10 chapters. Hands on exercises in SAP tools are available for members of the SAP University Alliance program and can be adapted to other popular tools as needed.
SECTION 1 DATA ANALYTICS BASICS
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CHAPTER 1: DATA ANALYTICS OVERVIEW |
SECTION 2 DATA FUNDAMENTALS
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CHAPTER 2: DATA ACQUISITION |
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CHAPTER 3: DIMENSIONAL DATA MODELING |
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CHAPTER 4: DATA EXTRACTION, TRANSFORMATION AND LOADING |
SECTION 3: REPORTING AND ANALYSIS
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CHAPTER 5: SLICING AND DICING |
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CHAPTER 6: DATA VISUALIZATION |
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CHAPTER 7: REPORTS AND DASHBOARDS |
SECTION 4: KNOWLEDGE DISCOVERY, PREDICTION AND DECISION MAKING
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CHAPTER 9: UNSUPERVISED MACHINE LEARNING |
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CHAPTER 10: TIME SERIES ANALYSIS AND FORECASTING |
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CHAPTER 11: PREDICTIVE MACHINE LEARNING |
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CHAPTER 12: ANALYTICS IN PRACTICE |
APPENDIX A: SQL
APPENDIX B: LSA FOR ETL
APPENDIX C: CHARTING EASY REFERENCE GUIDE
Instructors: Use your faculty email address to request a desk copy below
Practical Analytics Sample Syllabus 1H20
