Introduction to R for Business Intelligence - Softcover

Gendron, Jay

Softcover

ISBN 10: 1785280252 ISBN 13: 9781785280252

Publisher: Packt Publishing, 2016

Synopsis

Key Features

• Use this easy-to-follow guide to leverage the power of R analytics and make your business data more insightful.
• This highly practical guide teaches you how to develop dashboards that help you make informed decisions using R.
• Learn the A to Z of working with data for Business Intelligence with the help of this comprehensive guide.

Book Description

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.

What you will learn

• Extract, clean, and transform data
• Validate the quality of the data and variables in datasets
• Learn exploratory data analysis
• Build regression models
• Implement popular data-mining algorithms
• Visualize results using popular graphs
• Publish the results as a dashboard through Interactive Web Application frameworks

About this title

About the Author

Jay Gendron is an Associate Data Scientist with Booz Allen Hamilton. He is a business leader, artist, and author. He is dedicated to the idea that decision makers have more access to analytics than believed. His analytic work includes finding trends in startup and entrepreneurial communities, assessing the learning and sociological impacts of training systems, and describing business case analyses and process mining. Jay has a B.S.M.E. in Mechanical Engineering, an M.S. in Management of Technology, and an M.S. in Operations Research. He is a lifelong learner- a member of the first 40-person cohort to earn the Data Science Specialization Certificate by Johns Hopkins University on Coursera-and notes, "Education will never be the same." Jay is an award-winning speaker who has presented internationally; he volunteers with numerous not-for-profit organizations to contribute his data science skills and improve their operational insights. He is the founder of the "try.Py - Learn Python" meet-up.

Edition details

• Publisher: Packt Publishing
• Publication date: 2016
• Language: English
• ISBN 10: 1785280252
• ISBN 13: 9781785280252
• Binding: Paperback
• Number of pages: 228