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Test C2090-419: IBM InfoSphere QualityStage v8 Examination


Note: This test will be withdrawn on Dec 31 2013.
The replacement tests are: (000-304) IBM InfoSphere QualityStage v9.1 Solution Developer and (000-422) InfoSphere QualityStage v8.5


Methodology (5%)


  1. Describe the steps in data quality methodology.

  2. Business requirements as related to data quality

  3. Process sequence and why

  4. Define probabilistic matching versus deterministic matching.


Design Considerations (17%)


  1. Identify the steps for standardization.

  2. Given a scenario, demonstrate knowledge how to optimize QualityStage jobs using parallel concepts.

  3. Given a scenario, describe how to handle data from multiple countries for standardization.

  4. Describe initial vs. delta vs. real-time design considerations. (may use scenarios)

  5. Design QualityStage flow for real-time deployment

  6. Describe data structure considerations for source and target QualityStage jobs. (may use scenarios)


Investigation (10%)


  1. Given a scenario, demonstrate knowledge of investigation stage and types.

  2. Given a scenario, describe how word investigation results can be used.


Standardization/Addresses/Postal (12%)


  1. Describe the differences between address certification, verification, and standardization.

  2. Define what the standardization stage is and how to use it.

  3. Given a scenario, describe the purpose of standardization and what results are produced by the process.


Rule Sets (15%)


  1. Demonstrate knowledge of how to customize standardization rules.

  2. Demonstrate knowledge of the components of a rule and their functions.

  3. Demonstrate knowledge of managing standardization rules.


Matching (20%)


  1. Given a scenario, demonstrate knowledge of match concepts.

  2. Describe the match components.

  3. Given a scenario, describe how to review and tune a match.

  4. Demonstrate knowledge of match specification and pass re-usability.

  5. Given a scenario, demonstrate knowledge of match job design to achieve optimal performance.


Survive (10%)


  1. Describe the purpose of survive.

  2. Demonstrate knowledge of the different rule types for surviving data and when to use them.

  3. Describe how to implement a survive stage.


Setup & Troubleshooting (11%)


  1. Identify how to troubleshoot a QualityStage job.

  2. Describe how to configure data quality functionality.

  3. Describe QualityStage deployment considerations.

  4. Demonstrate knowledge of NLS/non-NLS install and its impact on QualityStage stages.




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