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C2090-424 - InfoSphere DataStage V11.3 Practice Exam Questions

C2090-424 - InfoSphere DataStage V11.3


About InfoSphere DataStage v11.3

This certification demonstrates that the successful candidate has important knowledge and skills necessary to professionally design and develop an efficient and scalable DataStage solution to a complex enterprise-level business problem; configure a scalable parallel environment including clustered and distributed configurations; collect, report on, and resolve issues identified through key application performance indicators; be proficient in extending the capabilities of the parallel framework using the provided APIs (build-ops and wrappers).


Prerequisite for the exam

Able to design and develop a scalable complex solution using an optimum number of stages.

Able to select the optimal data partitioning methodology.

Able to configure a distributed or non-symmetric environment.

Should be proficient with BuildOps and wrappers.

Should understand how to tune a parallel application to determine where bottlenecks exist and how to eliminate them.

Should understand basic configuration issues for all relational databases and be highly proficient in at least one.

Able to improve job design by implementing new product features in DataStage v11.3.

Able to monitor DataStage jobs via the Job Log and the Operations Console.


Course Outline

1. Configuration

Describe how to properly configure DataStage.


Identify tasks required to create and configure a project to be used for jobs.


Given a configuration file, identify its components and its overall intended purpose.


Demonstrate proper use of node pools.


2. Metadata


Demonstrate knowledge of framework schema.


Identify the method of importing, sharing, and managing metadata.


Demonstrate knowledge of runtime column propagation (RCP).


3. Persistent Storage


Explain the process of importing/exporting data to/from framework.


Demonstrate proper use of a Sequential File stage.


Demonstrate proper usage of Complex Flat File stage.


Demonstrate proper usage of FileSets and DataSets.


Demonstrate use of FTP stage for remote data.


Demonstrate use of restructure stages.


Identify importing/exporting of XML data.


Knowledge of balanced optimization for Hadoop and integration of oozie workflows.


Demonstrate proper use of File Connector stage.


Demonstrate use of DataStage to handle various types of data including unstructured, hierarchical, Cloud, and Hadoop.


4. Parallel Architecture


Demonstrate proper use of data partitioning and collecting.


Demonstrate knowledge of parallel execution.


5. Databases


Demonstrate proper selection of database stages and database specific stage properties.


Identify source database options.


Demonstrate knowledge of target database options.


Demonstrate knowledge of the different SQL input/creation options and when to use each.


6. Data Transformation


Demonstrate knowledge of default type conversions, output mappings, and associated warnings.


Demonstrate proper selections of Transformer stage vs. other stages.


Describe Transformer stage capabilities.


Demonstrate the use of Transformer stage variables.


Identify process to add functionality not provided by existing DataStage stages.


Demonstrate proper use of SCD stage.


Demonstrate job design knowledge of using runtime column propagation (RCP).


Demonstrate knowledge of Transformer stage input and output loop processing.


7. Job Components


Demonstrate knowledge of Join, Lookup and Merge stages.


Demonstrate knowledge of Sort stage.


Demonstrate understanding of Aggregator stage.


Describe proper usage of change capture/change apply.


Demonstrate knowledge of real-time components.


8. Job Design


Demonstrate knowledge of shared containers.


Describe how to minimize Sorts and repartitions.


Demonstrate knowledge of creating restart points and methodologies.


Explain the process necessary to run multiple copies of the source.


Knowledge of creating DataStage jobs that can be used as a service.


Knowledge of balanced optimization.


Describe the purpose and uses of parameter sets and how they compare with other approaches for parameterizing jobs.


Demonstrate the ability to create and use Data Rules using the Data Rules stage to measure the quality of data.


Demonstrate various methods of using DataStage to handle encrypted data.


9. Monitor and Troubleshoot


Demonstrate knowledge of parallel job score.


Identify and define environment variables that control DataStage with regard to added functionality and reporting.


Given a process list, identify conductor, section leader, and player process.


Identify areas that may improve performance.


Demonstrate knowledge of runtime metadata analysis and performance monitoring.


Ability to monitor DataStage jobs using the Job Log and Operations Console.


10. Job Management and Deployment


Demonstrate knowledge of DataStage Designer Repository utilities such as advanced find, impact analysis, and job compare.


Articulate the change control process.


Knowledge of Source Code Control Integration.


Demonstrate the ability to define packages, import, and export using the ISTool utility.


Demonstrate the ability to perform admin tasks with tools such as Directory Admin.


11. Job Control and Runtime Management


Demonstrate knowledge of message handlers.


Demonstrate the ability to use the dsjob command line utility.


Demonstrate ability to use job sequencers.


Create and manage encrypted passwords and credentials files.


Exam Pattern 

  • Exam Name: InfoSphere DataStage v11.3
  • Exam Code: C2090-424
  • Length of Time:  90 Minutes


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