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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

Building a sales query in MS SQL Server


Before we can start visualizing our amazing data in Tableau, we must first put together the query that will provide us that amazing data. We have been asked to put together a sales dashboard that highlights sales from different marketing promotions that have been initiated since the start of AdventureWorks. This promotional data is located in the Sales.SalesReason table in the data warehouse, as seen in the following screenshot:

These results show that there are ten different possible promotions that could have resulted in a sale. The actual sales data is in the Sales.SalesOrderHeader table but that table does not have the SalesReasonID for us to join sales to promotions. The SalesOrderHeader table has a SalesOrderID, as seen in the following script:

SELECT  
distinct [SalesOrderID] 
FROM [AdventureWorks2014].[Sales].[SalesOrderHeader] 

We will need to find a table that can tie SalesOrderID to SalesReasonID. Fortunately, we have a table...

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