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Practical Business Intelligence

You're reading from   Practical Business Intelligence Optimize Business Intelligence for Efficient Data Analysis

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Product type Paperback
Published in Dec 2016
Publisher Packt
ISBN-13 9781785885433
Length 352 pages
Edition 1st Edition
Languages
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Author (1):
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Ahmed Sherif Ahmed Sherif
Author Profile Icon Ahmed Sherif
Ahmed Sherif
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Table of Contents (16) Chapters Close

Practical Business Intelligence
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Introduction to Practical Business Intelligence FREE CHAPTER 2. Web Scraping 3. Analysis with Excel and Creating Interactive Maps and Charts with Power BI 4. Creating Bar Charts with D3.js 5. Forecasting with R 6. Creating Histograms and Normal Distribution Plots with Python 7. Creating a Sales Dashboard with Tableau 8. Creating an Inventory Dashboard with QlikSense 9. Data Analysis with Microsoft SQL Server

Chapter 5. Forecasting with R

R is a popular programming language for statisticians and data scientists. This is primarily due to its popularity with students and professors in the academic world. R is a free and open source language that can be taught in any statistics class with minimal difficulty.

Within the last couple of years, R has creeped into the business intelligence landscape due to the integration of R with enterprise and desktop visualization tools such as Microsoft Power BI and Tableau. During this same period, many academics transitioned from research into the corporate world, and with them came their knowledge of R. While R is known for its predictive capabilities, many are surprised to find that it is a great visualization tool with many libraries, made available by its vast community, such as ggplot2.

In addition to the influx of R into the workforce, the introduction of RStudio into the market in 2011 brought added exposure to R. As we noted earlier in Chapter 2, Web Scraping...

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