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Introduction to R for Business Intelligence

You're reading from   Introduction to R for Business Intelligence Profit optimization using data mining, data analysis, and Business Intelligence

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Product type Paperback
Published in Aug 2016
Publisher Packt
ISBN-13 9781785280252
Length 228 pages
Edition 1st Edition
Languages
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Author (1):
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Jay Gendron Jay Gendron
Author Profile Icon Jay Gendron
Jay Gendron
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Table of Contents (13) Chapters Close

Preface 1. Extract, Transform, and Load FREE CHAPTER 2. Data Cleaning 3. Exploratory Data Analysis 4. Linear Regression for Business 5. Data Mining with Cluster Analysis 6. Time Series Analysis 7. Visualizing the Datas Story 8. Web Dashboards with Shiny A. References
B. Other Helpful R Functions C. R Packages Used in the Book
D. R Code for Supporting Market Segment Business Case Calculations

Summary

You completed the first step in your journey and should be pleased with yourself as ETL is not trivial or simple. In this chapter, you learned how to execute an ETL process from start to finish. This includes knowing how to extract data from multiple sources, including databases. Then, you transformed the data with the dplyr package and exported the information into a file that could be loaded into a business system.

In the next chapter, you will learn how to clean data once it is loaded. You will see that, like ETL, data cleaning is a broad and multi-faceted aspect of business intelligence and analytics.

You have been reading a chapter from
Introduction to R for Business Intelligence
Published in: Aug 2016
Publisher: Packt
ISBN-13: 9781785280252
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