Essentials of Business Analytics 1st edition by Bhimasankaram Pochiraju, Sridhar Seshadri – Ebook PDF Instant Download/Delivery: 3319688367, 978-3319688367
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Product details:
ISBN 10: 3319688367
ISBN 13: 978-3319688367
Author: Bhimasankaram Pochiraju, Sridhar Seshadri
This comprehensive edited volume is the first of its kind, designed to serve as a textbook for long-duration business analytics programs. It can also be used as a guide to the field by practitioners. The book has contributions from experts in top universities and industry. The editors have taken extreme care to ensure continuity across the chapters.
The material is organized into three parts: A) Tools, B) Models and C) Applications. In Part A, the tools used by business analysts are described in detail. In Part B, these tools are applied to construct models used to solve business problems. Part C contains detailed applications in various functional areas of business and several case studies. Supporting material can be found in the appendices that develop the pre-requisites for the main text.
Every chapter has a business orientation. Typically, each chapter begins with the description of business problems that are transformed into data questions; and methodology is developed to solve these questions. Data analysis is conducted using widely used software, the output and results are clearly explained at each stage of development. These are finally transformed into a business solution. The companion website provides examples, data sets and sample code for each chapter.
Essentials of Business Analytics 1st Table of contents:
1. Introduction
Part I. Tools
2. Data Collection
3. Data Management—Relational Database Systems (RDBMS)
4. Big Data Management
5. Data Visualization
6. Statistical Methods: Basic Inferences
7. Statistical Methods: Regression Analysis
8. Advanced Regression Analysis
9. Text Analytics
Part II. Modeling Methods
10. Simulation
11. Introduction to Optimization
12. Forecasting Analytics
13. Count Data Regression
14. Survival Analysis
15. Machine Learning (Unsupervised)
16. Machine Learning (Supervised)
17. Deep Learning
Part III. Applications
18. Retail Analytics
19. Marketing Analytics
20. Financial Analytics
21. Social Media and Web Analytics
22. Healthcare Analytics
23. Pricing Analytics
24. Supply Chain Analytics
25. Case Study: Ideal Insurance
26. Case Study: AAA Airline
27. Case Study: InfoMedia Solutions
28. Introduction to R
29. Introduction to Python
30. Probability and Statistics
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Tags: Bhimasankaram Pochiraju, Sridhar Seshadri, Business Analytics


