E-book details

Introduction to R for Business Intelligence. Profit optimization using data mining, data analysis, and Business Intelligence

Introduction to R for Business Intelligence. Profit optimization using data mining, data analysis, and Business Intelligence

Jay Gendron

Ebook
Explore the world of Business Intelligence through the eyes of an analyst working in a successful and growing company. Learn R through use cases supporting different functions within that company. This book provides data-driven and analytically focused approaches to help you answer questions in operations, marketing, and finance.
In Part 1, you will learn about extracting data from different sources, cleaning that data, and exploring its structure. In Part 2, you will explore predictive models and cluster analysis for Business Intelligence and analyze financial times series. Finally, in Part 3, you will learn to communicate results with sharp visualizations and interactive, web-based dashboards.
After completing the use cases, you will be able to work with business data in the R programming environment and realize how data science helps make informed decisions and develops business strategy. Along the way, you will find helpful tips about R and Business Intelligence.
  • 1. Extract, Transform, and Load
  • 2. Data Cleaning
  • 3. Exploratory Data Analysis
  • 4. Linear Regression for Business
  • 5. Data Mining - Cluster Analysis
  • 6. Time Series Analysis
  • 7. Visualizing the Data’s Story
  • 8. Web Dashboards with Shiny
  • 9. Appendix A References
  • 10. Appendix B - Other Helpful R Functions
  • 11. Appendix C - R Packages Used in the Book
  • 12. Appendix D - R Code for Supporting Market Segment Business Case Calculations
  • Title: Introduction to R for Business Intelligence. Profit optimization using data mining, data analysis, and Business Intelligence
  • Author: Jay Gendron
  • Original title: Introduction to R for Business Intelligence. Profit optimization using data mining, data analysis, and Business Intelligence
  • ISBN: 9781785286513, 9781785286513
  • Date of issue: 2016-08-26
  • Format: Ebook
  • Item ID: e_3b5z
  • Publisher: Packt Publishing