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Data Warehousing Informatica - Interview Questions and Answers
Explain the concept of Reusable Transformation.

A reusable transformation in Informatica PowerCenter is a pre-built transformation object that can be used multiple times within different mappings. This concept promotes efficiency, consistency, and maintainability in ETL development.

Here's a breakdown:

Core Concept :

  • Instead of creating the same transformation logic repeatedly in different mappings, you can create a single, reusable transformation and then reference it as many times as needed.
  • This transformation is stored in the Informatica repository, making it accessible to all mappings within the repository.

Benefits of Reusable Transformations :

  • Reduced Development Time:
    • You only need to create the transformation logic once, saving time and effort.
  • Improved Consistency:
    • Reusable transformations ensure that the same transformation logic is applied consistently across all mappings.
  • Enhanced Maintainability:
    • If you need to change the transformation logic, you only need to modify the reusable transformation once, and the changes will be reflected in all mappings that use it.
  • Simplified Mapping Design:
    • Reusable transformations can simplify complex mapping designs by encapsulating frequently used logic.
  • Promotes Standardization:
    • Reusable transformations help in standardizing the ETL processes.

How it Works :

  1. Creation:
    • You create a transformation (e.g., Expression, Lookup, Filter) and save it as a reusable transformation in the repository.
  2. Usage:
    • You can then drag and drop the reusable transformation into any mapping.
    • When you place a reusable transformation into a mapping, it is displayed with a special icon, to denote that it is a reusable object.
  3. Modification:
    • If you modify the reusable transformation, the changes are automatically propagated to all mappings that use it.

Example :

  • Imagine you have a complex expression that performs data cleansing and standardization. You could create this expression as a reusable transformation and then use it in multiple mappings that require data cleansing.
  • Another example would be a lookup transformation that looks up country codes, and returns country names. This lookup would be used in many mappings, so making it reusable is very efficient.