tailieunhanh - Hands-On Microsoft SQL Server 2008 Integration Services part 47

Hands-On Microsoft SQL Server 2008 Integration Services part 47. Deploy and manage high-performance data transformation solutions across your enterprise using the step-by-step techniques in this fully revised guide. Hands-On Microsoft SQL Server 2008 Integration Services, Second Edition explains the tools and methods necessary to extract conclusive business intelligence from disparate corporate data. Learn how to build and secure packages, load and cleanse data, establish workflow, and optimize performance. Real-world examples, detailed illustrations, and hands-on exercises are included throughout this practical resource. . | 438 Hands-On Microsoft SQL Server 2008 Integration Services Figure 10-17 Configuring Audit transformation in auditing. This transformation uses the Advanced Editor to expose its properties. To store the count of rows into a variable you need to define a variable before you can use this task. The variable must be in the scope of the Data Flow task to which the transformation belongs. To count the rows in the data flow and update the variable value you simply select the variable in the VariableName field of the Component Properties tab. You can actually have multiple RowCount transformations writing to the same variable for instance if you are updating auditing information about loading of data rows you might choose to use same variable in multiple RowCount transformations. However you need be aware of the fact that the multiple RowCount transformations using same the variable could update variable value multiple times and hence your auditing could get wrong values as the variable will keep the last value that it is updated with. Chapter 10 Data Flow Transformations 439 Business Intelligence Transformations The Business Intelligence transformations enable you to maintain a Slowly Changing Dimension SCD perform data cleaning data standardization and text mining operations and run data mining prediction queries against data mining models. The Slowly Changing Dimension SCD transformation is slightly complex to understand but it provides a configuration wizard that makes the task of loading a dimension table much easier. You will work through a Hands-On exercise to use an SCD transformation and you will perform another Hands-On exercise to remove duplicates from data using Lookup Fuzzy Lookup and Fuzzy Grouping transformations. Slowly Changing Dimension Transformation SCD helps you manage slowly changing data attributes in a data warehouse. To describe this transformation clearly and for the benefit of those who are new in data warehousing let s start with some .