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Practical Business Intelligence

You're reading from  Practical Business Intelligence

Product type Book
Published in Dec 2016
Publisher Packt
ISBN-13 9781785885433
Pages 352 pages
Edition 1st Edition
Languages

Table of Contents (16) Chapters

Practical Business Intelligence
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. Introduction to Practical Business Intelligence 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

Summary


We have covered quite a bit in this chapter to get us started with both R and Python but our work will pay off as we move along with subsequent chapters. We went through two exercises to scrape data from GitHub using both R and Python. As can be seen, both tools have popular packages that allow for easy scraping of data. Both approaches were described in detail to allow you to find which process works better for you. Python is more generally known as a web scraping software tool; however, R has similar capabilities for similar tasks. Both approaches were presented to offer you more tools to keep in your toolbox. These are not the only packages that either programming language has to offer to allow for web scraping, but they are some of the more popular ones. Further investigation will show many other scraping packages such as scrapy for Python.

In the next chapter, we will begin our BI development with Microsoft Excel and PowerBI.

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