Informatica Interview Questions and Answers
Freshers / Beginner level questions & answers
Ques 1. What is Informatica PowerCenter?
Informatica PowerCenter is an ETL (Extract, Transform, Load) tool used for data integration and warehousing.
Ques 2. What is a Session in Informatica?
A session in Informatica is a task that represents the execution of a workflow. It is the smallest unit of work in a workflow.
Ques 3. What is a Repository in Informatica?
A repository in Informatica is a relational database that stores metadata and configuration information about the various objects managed by Informatica.
Ques 4. What is a Workflow in Informatica?
A workflow in Informatica is a set of instructions for the integration service to execute the tasks defined in a mapping.
Ques 5. What is the purpose of the Aggregator transformation?
The Aggregator transformation in Informatica is used to perform aggregate calculations such as sum, average, minimum, maximum, etc., on groups of data.
Ques 6. What is the purpose of a Sequence Generator transformation?
The Sequence Generator transformation in Informatica is used to generate unique sequence numbers for rows in a data set.
Ques 7. What are the different types of transformations in Informatica?
Informatica supports various transformations, including Aggregator, Filter, Router, Lookup, Expression, Joiner, and many others.
Ques 8. What is the purpose of a Source Qualifier transformation?
The Source Qualifier transformation in Informatica is used to specify properties for reading data from a relational or flat file source.
Ques 9. Explain the concept of a Filter transformation.
A Filter transformation in Informatica is used to filter rows based on specified conditions, allowing only the required rows to pass through.
Ques 10. Explain the concept of a Parameter File in Informatica.
A Parameter File in Informatica is a text file that contains parameter values used to replace placeholders in session and workflow properties at runtime.
Ques 11. What is the purpose of a Router transformation in Informatica?
A Router transformation in Informatica is used to filter data rows to different output groups based on specified conditions.
Ques 12. How can you create a reusable session in Informatica?
A reusable session in Informatica can be created by defining the session as reusable in the session properties and saving it to the repository for use in multiple workflows.
Ques 13. How can you handle null values in Informatica?
Null values in Informatica can be handled using functions like ISNULL and COALESCE, or through the use of NULL indicator ports in transformations.
Ques 14. Explain the concept of a Joiner transformation.
A Joiner transformation in Informatica is used to combine rows from two heterogeneous sources based on a common column, similar to an SQL join operation.
Intermediate / 1 to 5 years experienced level questions & answers
Ques 15. Explain the difference between ETL and ELT.
ETL (Extract, Transform, Load) is a process where data is extracted from source systems, transformed, and then loaded into a data warehouse. ELT (Extract, Load, Transform) is a process where data is first extracted and loaded into the target system, and then transformations are applied.
Ques 16. Explain the difference between a Mapping and a Mapplet.
A mapping is a set of source and target definitions linked by transformations, while a mapplet is a reusable object that contains a set of transformations.
Ques 17. Explain the concept of a Router transformation.
A Router transformation in Informatica is used to route data rows to different transformation logic based on specified conditions.
Ques 18. What is a Repository Service in Informatica?
The Repository Service in Informatica is responsible for managing connections to the repository and providing access to the metadata stored in the repository.
Ques 19. What is a Rank transformation, and how is it used?
A Rank transformation in Informatica is used to select the top or bottom 'n' rows based on a specified condition or column.
Ques 20. Explain the concept of a Lookup transformation.
A Lookup transformation in Informatica is used to look up data in a relational table or view based on a condition and retrieve related values.
Ques 21. What is the difference between a connected and an unconnected Lookup transformation?
A connected Lookup transformation is connected to the pipeline, while an unconnected Lookup is not connected to the pipeline and must be called by another transformation.
Ques 22. How is parameterization achieved in Informatica?
Parameterization in Informatica is achieved through the use of parameter files, which contain values that can be substituted into session and workflow properties at runtime.
Ques 23. Explain the concept of Partitioning in Informatica.
Partitioning in Informatica involves dividing the source data into subsets to be processed in parallel, improving session performance.
Ques 24. How can you handle errors in Informatica?
Errors in Informatica can be handled using error handling strategies such as redirecting rows, terminating the session, or sending errors to a separate target.
Ques 25. Explain the concept of a Normalizer transformation.
A Normalizer transformation in Informatica is used to convert columns with repeating groups into multiple rows, making data more readable and usable.
Ques 26. Explain the concept of Data Transformation Manager (DTM) in Informatica.
The Data Transformation Manager (DTM) in Informatica is responsible for the execution of tasks within a session, such as reading, transforming, and loading data.
Ques 27. How can you improve session performance in Informatica?
Session performance in Informatica can be improved by optimizing transformations, using partitioning, increasing cache size, and tuning session properties.
Ques 28. How does Informatica handle incremental data loading?
Informatica handles incremental data loading by comparing source and target data based on a specified key and loading only the changed or new records.
Ques 29. What is the purpose of a Debugger in Informatica?
The Debugger in Informatica is used for testing and debugging mappings by allowing step-by-step execution and inspection of data at various points.
Ques 30. What is a Transaction Control transformation?
A Transaction Control transformation in Informatica is used to commit or roll back transactions based on specified conditions in a session.
Ques 31. How can you handle slowly changing dimensions in Informatica?
Slowly Changing Dimensions (SCD) in Informatica can be handled using techniques such as Type 1 (overwrite), Type 2 (historical), and Type 3 (add new column).
Ques 32. What is the purpose of a Target Load Plan in Informatica?
A Target Load Plan in Informatica specifies the order in which target tables are loaded, providing control over the loading sequence in a session.
Ques 33. Explain the concept of a Sorter transformation.
A Sorter transformation in Informatica is used to sort data based on one or more columns before passing it to the target transformation.
Ques 34. Explain the concept of a Surrogate Key in Informatica.
A Surrogate Key in Informatica is a system-generated key used to uniquely identify rows in a dimension table, often replacing natural keys for efficiency.
Ques 35. What is the purpose of a Pre-Session Command in Informatica?
A Pre-Session Command in Informatica is used to execute commands or scripts before the session starts, allowing for custom initialization tasks.
Ques 36. What is the purpose of a Data Masking transformation?
The Data Masking transformation in Informatica is used to mask sensitive data in a mapping, ensuring that confidential information is not exposed.
Ques 37. What is the purpose of a LookUp cache in Informatica?
A LookUp cache in Informatica is used to store and reuse lookup data, improving performance by reducing the number of database queries.
Ques 38. What is the purpose of a Normalizer transformation in Informatica?
A Normalizer transformation in Informatica is used to transform data by converting columns with repeating groups into multiple rows, simplifying data processing.
Experienced / Expert level questions & answers
Ques 39. Differentiate between static and dynamic cache in Informatica.
Static cache is populated at the beginning of a session and does not change during the session, while dynamic cache can be updated during the session.
Ques 40. What is a Constraint-based Loading Order in Informatica?
Constraint-based loading order in Informatica ensures that data is loaded into the target in a specific order based on defined constraints between transformations.
Ques 41. How is Incremental Aggregation achieved in Informatica?
Incremental Aggregation in Informatica involves updating only the changed or new records in the source, reducing the processing load.
Ques 42. Explain the concept of a Dynamic Lookup Cache.
A Dynamic Lookup Cache in Informatica is created at runtime and allows the addition of new entries during the session.
Ques 43. What is a Persistent Cache in Informatica?
A Persistent Cache in Informatica is a type of cache that is stored on disk and can be reused across sessions, providing improved performance.
Ques 44. Explain the concept of a Data-driven session in Informatica.
In a Data-driven session in Informatica, the session properties and mappings are determined at runtime based on metadata, allowing dynamic control of the ETL process.
Ques 45. What is the purpose of a Unconnected Stored Procedure transformation?
The Unconnected Stored Procedure transformation in Informatica is used to execute stored procedures that are not connected to the pipeline and do not return a value.
Ques 46. Explain the concept of a Dynamic Partitioning in Informatica.
Dynamic Partitioning in Informatica allows the Informatica server to dynamically determine the number of partitions based on the available system resources.
Ques 47. What is a Lookup Override in Informatica?
A Lookup Override in Informatica allows you to override the default SQL query generated by the Lookup transformation to customize data retrieval.
Ques 48. Explain the concept of a Source Filter in Informatica.
A Source Filter in Informatica is used to filter rows at the source database level before they are read by the source qualifier, optimizing data extraction.
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