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    Copyright
    About the Authors
    Introduction
    Ch. 1. Installing SQL Server 2005 Business Intelligence Tools
    Ch. 2. Configuring SQL Server 2005 Business Intelligence Components
    Ch. 3. Migrating to SQL Server 2005 Business Intelligence Components
    Ch. 4. Developing SSIS Packages
    Ch. 5. Debugging and Error Handling with SSIS Packages
    Before You Begin
    Lesson 1. Configuring Package Transactions and Checkpoints
    Lesson 2. Identifying Package Status and Handling Task Errors
    Lesson 3. Handling Data Flow Errors and Debugging
    Case Scenario: Troubleshooting and Handling Errors in SSIS Packages
    Chapter Summary
    Ch. 6. Developing SSAS Cubes
    Ch. 7. Extending SSAS Cubes
    Ch. 8. Defining SSAS Storage, Partitions, and Aggregations
    Ch. 9. Developing SSAS Data Mining Models
    Ch. 10. Developing SSRS Reports
    Ch. 11. Formatting and Extending SSRS Reports
    Ch. 12. Deploying and Configuring SSIS Packages
    Ch. 13. Deploying and Processing SSAS Objects
    Ch. 14. Deploying and Scheduling SSRS Reports
    Ch. 15. Securing and Executing SSIS Packages
    Ch. 16. Administering and Securing SSAS Cubes
    Ch. 17. Securing and Querying SSAS Data Mining Models
    Ch. 18. Managing and Securing SSRS Reports
    Case Scenario Answers
    System Requirements
    Exam 70-445: Microsoft® SQL Server™ 2005 Business Intelligence—Implementation and Maintenance
    Additional Windows (R2) Resources for Administrators
    Additional SQL Server Resources for Administrators
    Prepare for Certification with Self-Paced Training Kits: Official Exam Prep Guides—Plus Practice Tests
    2007 Microsoft® Office System Resources for Developers and Administrators
    Additional Resources for IT Professionals from Microsoft Press
    Microsoft® SQL Server™ 2005 Training Kits
    Index
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    Help

    Chapter 5. Debugging and Error Handling ... > Handling Data Flow Errors and Debugg...

    Lesson 3. Handling Data Flow Errors and Debugging

    Estimated lesson time: 45 minutes


    In the real world, no data source is perfect. This means that you will need to handle anomalies and bad data as you process data in your SSIS data flow. Rather than having to fail a data flow, SSIS includes the ability to route the bad rows away from the data flow and handle the data problem without affecting the good rows. Furthermore, within the data flow, you can pause the execution and monitor the actual data as it is flowing through the SSIS engine.


      

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