Business Analytics: Data Science for Business Problems
- Length: 425 pages
- Edition: 1
- Language: English
- Publisher: Springer
- Publication Date: 2022-02-04
- ISBN-10: 3030870227
- ISBN-13: 9783030870225
- Sales Rank: #0 (See Top 100 Books)
This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems. These are a foundational understanding of:
1. statistical, econometric, and machine learning techniques;
2. data handling capabilities;
3. at least one programming language.
Practical in orientation, the volume offers illustrative case studies throughout and examples using Python in the context of Jupyter notebooks. Covered topics include demand measurement and forecasting, predictive modeling, pricing analytics, customer satisfaction assessment, market and advertising research, and new product development and research. This volume will be useful to business data analysts, data scientists, and market research professionals, as well as aspiring practitioners in business data analytics. It can also be used in colleges and universities offering courses and certifications in business data analytics, data science, and market research.
Cover Front Matter Part I. Beginning Analytics 1. Introduction to Business Data Analytics: Setting the Stage 2. Data Sources, Organization, and Structures 3. Basic Data Handling 4. Data Visualization: The Basics 5. Advanced Data Handling: Preprocessing Methods Part II. Intermediate Analytics 6. OLS Regression: The Basics 7. Time Series Analysis 8. Statistical Tables Part III. Advanced Analytics 9. Advanced Data Handling for Business Data Analytics 10. Advanced OLS for Business Data Analytics 11. Classification with Supervised Learning Methods 12. Grouping with Unsupervised Learning Methods Back Matter
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