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IBM Assessment: InfoSphere DataStage v8.5 Sample Questions:

1. In which two situations is it appropriate to use a Sparse Lookup? (Choose two.)

A) When accessing DB2 data using the DB2 API stage.
B) When the output of the Lookup stage needs to be hashed partitioned.
C) When reference data is significantly larger than the streaming data (100:1).
D) When invoking a stored procedure within a database per row in the streaming link.

2. In a Transformer Stage you have a nullable input column that is mapped to a non-nullable output column. What two techniques can be used to handle NULL values? (Choose two.)

A) IF input_column = NULL THEN 'unknown' ELSE input_column.
B) NullToValue(input_column, 'unknown').
C) IF input_column = '' THEN 'unknown' ELSE input_column.
D) IF IsNULL(input_column) THEN 'unknown' ELSE input_column.

3. Which two job design techniques can be used to provide unique names to sequential output files that are used in multi-instance jobs? (Select two)

A) Create the file name(s) from values contained in a value file.
B) Use the file name(s) from values contained in the data stream.
C) Prepend/append the Invocation ID to the file name.
D) Use parameters to identify file names.

4. How is DataStage Table Metadata shared among DataStage projects?

A) Import another copy of the table metadata into the project where it is required.
B) Use the "Shared Table Creation Wizard" to create a copy of the table in the shared repository.
C) Export DataStage Table Definitions from one project and importing them into another project.
D) DataStage Tables cannot be shared between projects.
E) Use the Import/Export Manager to move the DataStage Table Definition to the projects where it is needed.

5. Which two features of Data Sets make them suitable for job restart points? (Choose two.)

A) They are compressed to minimize storage space.
B) They are persistent.
C) They use the same data types as the parallel framework.
D) They are indexed to improve access.

Solutions: