Book Image

SQL Server 2017 Integration Services Cookbook

By : Christian Cote, Dejan Sarka, David Peter Hansen, Matija Lah, Samuel Lester, Christo Olivier
Book Image

SQL Server 2017 Integration Services Cookbook

By: Christian Cote, Dejan Sarka, David Peter Hansen, Matija Lah, Samuel Lester, Christo Olivier

Overview of this book

SQL Server Integration Services is a tool that facilitates data extraction, consolidation, and loading options (ETL), SQL Server coding enhancements, data warehousing, and customizations. With the help of the recipes in this book, you’ll gain complete hands-on experience of SSIS 2017 as well as the 2016 new features, design and development improvements including SCD, Tuning, and Customizations. At the start, you’ll learn to install and set up SSIS as well other SQL Server resources to make optimal use of this Business Intelligence tools. We’ll begin by taking you through the new features in SSIS 2016/2017 and implementing the necessary features to get a modern scalable ETL solution that fits the modern data warehouse. Through the course of chapters, you will learn how to design and build SSIS data warehouses packages using SQL Server Data Tools. Additionally, you’ll learn to develop SSIS packages designed to maintain a data warehouse using the Data Flow and other control flow tasks. You’ll also be demonstrated many recipes on cleansing data and how to get the end result after applying different transformations. Some real-world scenarios that you might face are also covered and how to handle various issues that you might face when designing your packages. At the end of this book, you’ll get to know all the key concepts to perform data integration and transformation. You’ll have explored on-premises Big Data integration processes to create a classic data warehouse, and will know how to extend the toolbox with custom tasks and transforms.
Table of Contents (18 chapters)
Title Page
About the Authors
About the Reviewers
Customer Feedback

Reading data profiling XML results with the Script task

In this recipe, you will read the XML file produced by the Data Profiling task and use the Script task to read the regular expressions extracted and store them in package variables.

Getting ready

This recipe assumes that you have finished the first recipe of Chapter 5,Dealing with Data Quality, and have the results of the Data Profiling task at your hand.


For your convenience, the results of the Data Profiling task needed for this recipe are provided in the DataProfiling.xml file.

How to do it...

  1. Add a new package to the AdventureWorksETL project. Rename the default package RegExValidation.dtsx.
  2. Create two package variables. Name them EmailRegEx1 and EmailRegEx2. Use the String data type for both variables.
  3. Drag the Script task to your control flow. Rename it ReadPatterns.
  4. Open the editor for this task. On the Script page of the Script Task Editor, make sure that the Visual C# language is selected. Add the User::EmailRegEx1 and User::EmailRegEx2...