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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

Concepts

Database Administration

Authors (6):

Christian Cote

Dejan Sarka

David Peter Hansen

Matija Lah

Samuel Lester

Christo Olivier

View More author details

Table of Contents (18) Chapters

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

Designing patterns to load dimensions of a data warehouse

The difference between these patterns is the way historical data is stored in the dimensions. We call them Slowly Changing Dimensions (SCD). The following points give an overview of various SCD types:

Type 0: This retains the original. This means that any changes to a specific member of the dimension will result in a new member inserted with new values. As opposed to SCD type 2, there's no concept of the current version or start and end date of a row. This SCD type is rarely used.
Type 1: This overwrites changes, no history is kept. For example, let's say we have a person's marital status attribute in a claimant dimension. If the initial value at insertion was Single, the attribute value is updated to Married when the person gets married.
Type 2: This keeps history (versioning). A bunch of system columns are added to the dimension:
- The start and end date of the dimension member (row). Usually, the start date equals the date when the...

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Authors (6)

Christian Cote

Christian Cote is an IT professional with more than 15 years of experience working in a data warehouse, Big Data, and business intelligence projects. Christian developed expertise in data warehousing and data lakes over the years and designed many ETL/BI processes using a range of tools on multiple platforms. He's been presenting at several conferences and code camps. He currently co-leads the SQL Server PASS chapter. He is also a Microsoft Data Platform Most Valuable Professional (MVP).

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Dejan Sarka

Dejan Sarka, MCT and Microsoft Data Platform MVP, is an independent trainer and consultant who focuses on the development of database and business intelligence applications. He is the founder of the Slovenian SQL Server and .NET Users Group.

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David Peter Hansen

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Matija Lah

Matija Lah has more than 18 years of experience working with Microsoft SQL Server, mostly from architecting data-centric solutions in the legal domain. His contributions to the SQL Server community have led to him being awarded the MVP Professional award (Data Platform) between 2007 and 2017/2018. He spends most of his time on projects involving advanced information management and natural language processing, but often finds time to speak at events related to Microsoft SQL Server where he loves to share his experience with the SQL Server platform.

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Samuel Lester

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Christo Olivier

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