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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

Connecting Excel to SQL Statements


Just as there are tables in SQL Server within our AdventureWorks2014 database for us to query on, there are also predefined views that are available for us to use; for all practical purposes, these views behave exactly the same as tables. The views are available at the following location within SQL Server:

The following script can be used to pull store information such as postal codes and the number of employees:

 SELECT  
 StoreAddress.City as 'City' 
,StoreAddress.Name as 'Store Name' 
,StoreAddress.PostalCode as 'Postal Code' 
,sum(StoreDemo.NumberEmployees) as 'Number of Employees' 
  
 FROM [AdventureWorks2014].[Sales].[vStoreWithAddresses] as StoreAddress 
 INNER JOIN [AdventureWorks2014].[Sales].[vStoreWithDemographics] StoreDemo on 
 StoreAddress.BusinessEntityID=StoreDemo.BusinessEntityID  
  
 Group by  
 StoreAddress.City 
,StoreAddress.Name 
,StoreAddress.PostalCode 
 order...
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