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SQL Server 2017 Integration Services Cookbook

You're reading from  SQL Server 2017 Integration Services Cookbook

Product type Book
Published in Jun 2017
Publisher Packt
ISBN-13 9781786461827
Pages 558 pages
Edition 1st Edition
Languages
Authors (6):
Christian Cote Christian Cote
Profile icon Christian Cote
Dejan Sarka Dejan Sarka
Profile icon Dejan Sarka
David Peter Hansen David Peter Hansen
Profile icon David Peter Hansen
Matija Lah Matija Lah
Profile icon Matija Lah
Samuel Lester Samuel Lester
Profile icon Samuel Lester
Christo Olivier Christo Olivier
Profile icon Christo Olivier
View More author details
Toc

Table of Contents (18) Chapters close

Title Page
Credits
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. SSIS Setup 2. What Is New in SSIS 2016 3. Key Components of a Modern ETL Solution 4. Data Warehouse Loading Techniques 5. Dealing with Data Quality 6. SSIS Performance and Scalability 7. Unleash the Power of SSIS Script Task and Component 8. SSIS and Advanced Analytics 9. On-Premises and Azure Big Data Integration 10. Extending SSIS Custom Tasks and Transformations 11. Scale Out with SSIS 2017

Preparing a Naive Bayes SSAS data mining model


In this recipe, you will determine the factors that influence buying bikes. You will use the Naive Bayes algorithm with the training set you prepared in the previous recipe.

Getting ready

For this recipe, you need to have SSAS installed in multidimensional and data mining mode. You also need to finish the first recipe in this chapter.

How to do it...

  1. In SSDT, add a new analysis services multidimensional and data mining project to the Chpater08 solution. Name it Ch08NaiveBayes.
  2. Create a new data source using the AdventureWorksDW2014 database. Use the Native OLE DB\SQL Server Native Client 11.0 provider. Use a Windows user that has permission to read the data. Use the default name for the data source.
  3. Create a new data source view based on the data source created in step 2. Select the TMTrainingSet and TMTestSet tables created in the first recipe of this chapter for the training and test sets. Use the default name for the data source view.
  4. Set the CustomerKey...
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