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Microsoft SQL Server 2012 Integration Services: An Expert Cookbook

Microsoft SQL Server 2012 Integration Services: An Expert Cookbook

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Microsoft SQL Server 2012 Integration Services: An Expert Cookbook

Microsoft SQL Server 2012 Integration Services: An Expert Cookbook

3.9 (12)

Overview of this book

SQL Server Integration Services (SSIS) is a leading tool in the data warehouse industry - used for performing extraction, transformation, and load operations. This book is aligned with the most common methodology associated with SSIS known as Extract Transform and Load (ETL); ETL is responsible for the extraction of data from several sources, their cleansing, customization, and loading into a central repository normally called Data Warehouse or Data Mart.Microsoft SQL Server 2012 Integration Services: An Expert Cookbook covers all the aspects of SSIS 2012 with lots of real-world scenarios to help readers understand usages of SSIS in every environment. Written by two SQL Server MVPs who have in-depth knowledge of SSIS having worked with it for many years.This book starts by creating simple data transfer packages with wizards and illustrates how to create more complex data transfer packages, troubleshoot packages, make robust SSIS packages, and how to boost the performance of data consolidation with SSIS. It then covers data flow transformations and advanced transformations for data cleansing, fuzzy and term extraction in detail. The book then dives deep into making a dynamic package with the help of expressions and variables, and performance tuning and consideration.
Table of Contents (23 chapters)
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Microsoft SQL Server 2012 Integration Services: An Expert Cookbook
Credits
Foreword
About the Authors
About the Reviewers
www.PacktPub.com
Preface
1
Index

Change Data Capture


An important concern, when dealing with data integration, is to detect which data has changed since the last time we accessed the source data location. It's required to avoid affecting source system operations and to make the process of reading data from a source location faster. It's better to get just the changed data, than extracting all the data.

Change Data Capture (CDC) feature was included in SQL 2008 version. It provides the possibility to detect change in data in a database. CDC seems to be one of the most powerful approaches as compared to the other known approaches such as audit columns, timed extracts, database log scraping, check sums, and others, CDC has low impact (does not require any changes into the main tables), low overhead (runs asynchronously, unlike the triggers used in the audit columns approach (the most often used approach)), is also easy to use.

In spite of using the Datetime field to get the data change ranges, CDC uses a unique and sequence...

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