What is ETL?
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.
The ETL Testing
Process
Because data is so important to a successful business, poor
performance or inaccurate procedure can cost time and money. Therefore, ETL
testing is designed to ensure that the person in charge of the ETL process has
the best understanding of it possible. By asking questions of new applicants or
current employees ETL testing will ensure the most efficient and up to date
abilities of the person and the process.
ETL testing will also help to ensure the best work possible
is being done and will confirm the correctness of data being transformed. This
is measured against the rules and requirements of the company itself. It also
verifies that the transformed data can loaded without any loss of information,
is used to validate the accuracy of reports, ensures that the process meets
performance requirements, and finally, is used to evaluate the entire reporting
structure. If you plan on stepping into a role that will require an ETL
interview check, out Udemy’s course on data extraction tips and tricks, which
can help you learn great methods to help you prepare for your burgeoning
career.
Key Challenges
- How to validate millions of records across heterogenious data sources such as flat files, databases (eg. Oracle, DB2, SQL Server), Hadoop?
- How to automate ETL Testing without writing custom code?
- How to automate regression testing of ETL?
- How to test Incremental ETL?
- How to validate 100% of the data and not just sample datasets?
- How to increase my ETL test coverage?
- How to reduce the ETL and data testing costs?
- How to compare report output with the data in the source system (end-to-end testing)?
- How to test that the data in flat files got loaded into database properly? How to validate that the incoming files are conforming to the data quality requirements?
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