Mappings & Transformations Flashcards

What is pushdown optimization in Informatica Cloud Data Integration?

Answer: A technique that pushes transformation logic to the source database for native processing, reducing data movement

Pushdown optimization pushes transformation logic down to the source or target database so the database engine executes the logic natively, significantly reducing data movement and improving performance.

What is a dynamic mapping in Informatica Cloud?

Answer: A mapping that adapts to source or target schema changes at runtime without requiring redesign

A dynamic mapping can handle schema changes at runtime without requiring you to modify and redeploy the mapping design, making it flexible for evolving data structures.

In Informatica Cloud, what is the purpose of the Data Masking transformation?

Answer: To replace sensitive data with realistic but fictitious values for testing or privacy compliance

The Data Masking transformation replaces sensitive production data with masked, realistic but fictitious values, supporting test data creation and compliance with data privacy regulations such as GDPR.

What is a Union transformation in Informatica Cloud used for?

Answer: To merge multiple input pipelines with compatible schemas into a single output stream

The Union transformation merges multiple input pipelines that share the same port structure into a single output pipeline, similar to SQL UNION ALL, without deduplication.

Which Sorter transformation property in Informatica Cloud specifies where temporary files are stored when data volume exceeds available memory?

Answer: Work Directory

The Work Directory property specifies the file system path where the Sorter transformation writes temporary files during disk-based sorting when data volume exceeds the configured memory cache.

What is the Normalizer transformation in Informatica Cloud designed to handle?

Answer: To convert denormalized data with repeating column groups into normalized relational rows

The Normalizer transformation converts denormalized data containing repeating column groups or multi-occurring data into normalized, relational rows suitable for loading into structured targets.

In Informatica Cloud mappings, what is the purpose of the Java transformation?

Answer: To execute custom Java code within a mapping for complex logic not available as built-in transformations

The Java transformation allows developers to write and execute custom Java code inside a mapping, enabling complex transformation logic that cannot be achieved with standard built-in transformations.