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Mastering SQL Server 2017

You're reading from  Mastering SQL Server 2017

Product type Book
Published in Aug 2019
Publisher Packt
ISBN-13 9781838983208
Pages pages
Edition 1st Edition
Languages
Concepts
Authors (5):
Miloš Radivojević Miloš Radivojević
Profile icon Miloš Radivojević
Dejan Sarka Dejan Sarka
Profile icon Dejan Sarka
William Durkin William Durkin
Profile icon William Durkin
Christian Cote Christian Cote
Profile icon Christian Cote
Matija Lah Matija Lah
Profile icon Matija Lah
View More author details
Toc

Table of Contents (20) Chapters close

Title Page
Copyright Contributors About Packt Preface 1. Introduction to SQL Server 2017 2. SQL Server Tools 3. JSON Support in SQL Server 4. Stretch Database 5. Temporal Tables 6. Columnstore Indexes 7. SSIS Setup 8. What Is New in SSIS 2016 9. Key Components of a Modern ETL Solution 10. Dealing with Data Quality 11. Unleash the Power of SSIS Script Task and Component 12. On-Premises and Azure Big Data Integration 13. Extending SSIS Custom Tasks and Transformations 14. Scale Out with SSIS 2017 1. Other Books You May Enjoy

Introduction

Business intelligence projects often reveal previously unseen issues with the quality of the source data. Dealing with data quality includes data quality assessment, or data profiling, data cleansing, and maintaining high quality over time.

In SSIS, the data profiling task helps you find unclean data. The data profiling task is not like the other tasks in SSIS because it is not intended to be run over and over again through a scheduled operation. Think about SSIS as being the wrapper for this tool. You use the SSIS framework to configure and run the data profiling task, and then you observe the results through the separate data profile viewer. The output of the data profiling task will be used to help you in your development and design of the ETL and dimensional structures in your solution. Periodically, you may want to rerun the data profile task to see how the data...

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