What is ETL (extract, transform, and load) Testing?
ETL (extract, transform, and load) Testing Interview Questions
1. What is ETL (extract, transform, and load) Testing?
ETL - extract, transform, and load. Extracting data from outside source systems. Transforming raw data to make it fit for use by different departments. Loading transformed data into target systems like data mart or data warehouse.
etl testing interview questionsETL systems are used by businesses to integrate data from multiple sources. These software systems are key components in ensuring that your company is processing its data efficiently, allowing your business to run smooth and without interruption.
ETL stands for ‘extraction, transforming, and loading.’ This is the process by which data is taken from various sources, such as database servers, and transformed to fit with your business’s operational needs. This step involves assessing the quality levels of the data. Once that information has been assessed, it is then loaded into your company’s database, referred to as a warehouse. The process of ETL allows a business to collect important data, change it to fit their goals and models, and then store it for use. In a world of digital enterprise, it is a critical part of running an effective and efficient business.
ETL ( Extract Transformation and Load)testing is different from Database testing or backend testing both in terms of complexity and scope and hence requires a different approach as against conventional testing. The methodology
primarily aims at identifying and mitigating existing data defects and general errors occurring prior to processing of data for analytics and reporting.
The ETL Testing Methodology includes following steps:
Understanding of data to be reported
Understanding and review of data model
Understanding and review of source to target mappings (transformations)
Data Quality Assessment of Source data
Schema testing (source and target)
Verify Data completeness
Verification of transformation rules
Comparison of sample data between source and target
Checking of referential integrities and relations (primary key foreign key)
Data Quality checks on target warehouse
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