Interview Questions and Answers

A Surrogate Key is a unique identifier for a record in a data warehouse. It is typically a system-generated key used to maintain data integrity and enable efficient data warehousing operations.

Example:

In DataStage, a Surrogate Key may be generated using a Sequential File stage or a database sequence.

Errors in a DataStage job can be handled using reject links, exception handling stages, and job control activities. Reject links allow you to redirect erroneous rows, and exception handling stages enable you to define actions for specific error scenarios.

Example:

If a record violates a data constraint, you can route it to an error table using a reject link for further analysis.

A Shared Container is a reusable set of stages and links that can be shared across multiple DataStage jobs. It promotes code reuse and simplifies maintenance.

Example:

You can create a Shared Container containing common data cleansing logic and reuse it in multiple jobs.

The Data Click stage is used for capturing and handling changes in data over time. It helps in the implementation of slowly changing dimensions in a data warehouse.

Example:

You can use the Data Click stage to identify and handle changes in customer addresses over time.

Performance optimization in DataStage involves using parallel processing, efficient data partitioning, optimizing data storage, and leveraging appropriate indexing in databases.

Example:

By partitioning the data based on a key and using parallel processing, you can significantly improve job performance.

A Shared Container Variable is a variable defined within a Shared Container and is accessible by all jobs using that container. It differs from a Job Parameter, which is specific to a single job.

Example:

You can use a Shared Container Variable to store configuration information shared across multiple jobs.

The Change Capture stage is used to identify and capture changes in data between two data sets. It is often used in incremental data extraction scenarios.

Example:

You can use the Change Capture stage to capture changes in customer data since the last extraction and update the data warehouse accordingly.