ETL VS DATABASE TESTING
Differences between the ETL and the Database Testing
ETL and database testing involve data validation, but both are not same. ETL testing is usually performed on data in a data warehouse, whereas database testing performed on transactional systems. Data comes from different applications into the transactional database.
Operations performed in ETL Testing
ETL testing involves the following operations:
- Validation of data movement from source to the target system.
- Data count verification in the source and target system.
- ETL testing verifies the transformation, extraction as per requirement and expectation.
- ETL testing ensures that data loads within an expected time frame to improve the scalability and performance.
The operation performed in Database Testing
Database testing focuses on data accuracy, the correctness of data, and valid values.
Database testing performs the following operations:
- Database testing focuses on verifying the column in a table has valid data values.
- To verify whether the primary or foreign key is maintained, database testing used.
- Database testing verifies whether the data is missing in the column. Here, we will check there are any null values exist in a column which should have a valid value.
- We are verifying the accuracy of data in columns.
For example, column of number of months shouldn't have a value greater than 12.
||ETL testing is performed for data extraction, transform and loading for BI reporting.
||Database testing is performed to validate and integrate the data.
||ETL testing used for information, forecasting, and analytical reporting.
||This testing is used to integrate the data from multiple applications and server impact.
||ETL testing contains historic data and not in a business flow environment.
||ETL testing contains the transactional system where the flow of business occurs.
||The multidimensional method used.
||ER method used.
||ETL testing applied to OLAP systems.
||Database testing is used in OLTP system.
||ETL using the data type de-normalized data with fewer joins, more indexes, and aggregations.
||The database used normalized data with joins.
||QuerySurge, Informatica, etc. tools used.
||QTP, Selenium tools used in database testing.