Cognizant ETL Developer Interview Questions and Answers

Filter stage is used in ETL processes to selectively pass or reject data based on specified criteria.

• Filter stage helps in removing unwanted data from the input dataset.

• It can be used to apply conditions like filtering out duplicate records, selecting specific columns, or excluding certain values.

• For example, a filter stage can be used to only pass records where the sales amount is greater than $1000.

Transform stage is used in ETL process to apply business rules, clean and enrich data before loading into target database.

• Transform stage is used to apply business rules to the data.

• It is used to clean and standardize data before loading into the target database.

• Transform stage can also be used to enrich data by combining multiple sources or adding calculated fields.

• Examples include converting data types, removing duplicates, and aggregating data.

ETL is Extract, Transform, Load where data is extracted, transformed, and loaded into a data warehouse. ELT is Extract, Load, Transform where data is extracted, loaded into a data warehouse, and then transformed.

• ETL involves extracting data from source systems, transforming it according to business rules, and loading it into a data warehouse.

• ELT involves extracting data from source systems, loading it into a data warehouse, and then transforming it as needed.

• ETL is suitable f...read more

Sort stage is used in ETL processes to sort data based on specified criteria before loading it into the target system.

• Sort stage helps in arranging data in a specific order for better analysis and reporting

• It can be used to remove duplicates from data before loading

• Sorting can be done based on multiple columns or expressions

• Example: Sorting customer data based on their purchase amount before loading into a data warehouse

To create a parallel job, use parallel processing techniques to divide tasks into smaller subtasks that can be executed simultaneously.

• Identify tasks that can be executed independently and in parallel

• Use parallel processing techniques such as multi-threading or distributed computing

• Implement parallel job using ETL tools like Informatica or Talend

• Monitor and optimize parallel job performance to ensure efficient execution

SCD Type 1 in IICS involves overwriting existing data with new data without maintaining historical changes.

• In IICS, use the Mapping Designer to create a mapping that loads data from source to target.

• Use a Lookup transformation to check if the record already exists in the target table.

• If the record exists, update the existing record with new data using an Update Strategy transformation.

• If the record does not exist, insert the new record into the target table.

• Ensure that the ma...read more