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In today’s era, the demand for Database Warehouse testing is increasing very frequently. In the business world and IT industry, there are considerable opportunities in ETL Testing, because to protect data from and the daily maintenance of data is essential. ETL testing is required for day to day maintenance, integrity, and consistency of Data. From big business Enterprises to small-scale companies everyone wants to maintain their data integrity and consistency.
ETL means Extract, Transform, and Load.
ETL testing is done to make sure that the data which is loaded from source to the destination after the business transformation is accurate. In this type of testing, information is verified at various stages between the source and target destination.
ETL Testing process is similar to all the other types of testing performed.
i) Analyzing requirements and data sources.
ii) Data acquisition
iii) Implement dimensional Modelling and business logic
iv) Populate and build data
v) Building Reports
This testing is performed when data is being transferred into production systems. So it’s important to make sure that the data being transformed is validated completely before being turned to production.
This type of testing validates the data being extracted to the new application or 0repository is the same as the data in a repository or old application. This type of ETL testing can be automatically generated, saving test development time
Basically in Metadata testing tester has to validate the source and target tables corresponding to documents.
To validate all the data is loaded to the target source is done in this type of testing. Testing like checking Aggregate functions, validating count is data completeness testing.
This type of testing is done to check the accuracy of data being loaded and transformed
In this type of testing, the tester needs to run multiple SQL queries for each row to verify the transformation rules. It cannot be achieved by writing on one source SQL query and comparing the output with the target
# Data Quality Tests checks the quality of syntax and reference tests. Data Quality testing is done to avoid any error due to the order number or date during the business process.
# Tests of Syntax: It reports dirty data, based on invalid characters, a character pattern, wrong upper or lower case order, etc.
# Tests of Reference: It will check the data according to the data model. For example Customer ID
# Data quality testing includes date check, number check, data check, precision check, null check, etc.
To validate the data integrity of old and new data with the addition of new data, this testing is done. All the inserts and updates are getting processed as expected during incremental ETL process are checked with this type of testing.
All the navigation or GUI aspects of the front end reports are checked with this type of testing
For many enterprises, ETL is the challenge, but it is beneficial for the organization. It is necessary to protect your data from loss and keep updating the data daily. Data is a very crucial thing, and frequently changes in data warehouse increase the need for ETL Testing. It is necessary to clearly define the testing processes and security alliance between development, operations, and the business.