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IBM Certified Solution Developer - IBM InfoSphere DataStage Sample Questions:

1. Identify the two statements that are true about the functionality of the XML Pack 3.0. (Choose two.)

A) XML Stage can be found in the Database folder on the palette.
B) It includes the XML Input, XML Output, and XML Transformer stages.
C) XML Stages are Plug-in stages.
D) Uses a unique custom GUI interface called the Assembly Editor.
E) A single XML Stage, which can be used as a source, target, or transformation.

2. Modular development techniques should be used to maximize re-use of DataStage jobs and components. Which statement represents Modular Development techniques?

A) Job parameterization allows a single job design to process similar logic instead of creating multiple copies of the same job.
B) Create a standard directory structure inside of the DataStage project directory for source and target files.
C) Job parameters should be used in Job Names.
D) Hard code the Invocation ID to improve development process.

3. When using Runtime Column Propagation, which two stages require a schema file? (Choose two.)

A) DB2 Connector stage
B) Sequential File stage
C) Column Import stage
D) Peek stage
E) Pivot stage

4. You are editing the configuration file. Which statement is true about file system efficiency?

A) In a clustered environment where NAS is used for a common storage, you must specify the internal disk for scratch disk.
B) Creating scratch disk spaces on an internal disk rather than on an NFS drive improves sort performance.
C) Using multiple scratch spaces in a logical node improves performance.
D) For the resource disk, it is best to use the partition where the engine is installed.

5. Which statement is true about improving job performance when using Balanced Optimization?

A) If the job contains an Aggregator stage, data reduction stages will be pushed into a target data server by default.
B) To ensure that a particular stage can only be pushed into a source or target connector, you can set the Stage Affinity property to source or target.
C) Balance optimization attempts to balance the work between the source server, target sever, and the job.
D) Convert a job to use bulk staging tables for Big Data File stages.

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