ETL is a process that gathers and transforms various kinds of data. Once the data transformation is over, ETL sends the data over to the data warehouse. With ETL, you can move multiple pieces of data all across different sources, locations, and evaluation tools. It is why ETL has become a force to reckon with when it comes to business intelligence. ETL has become more extensive and effective when it comes to executing data management strategies.
On the other hand, database testing has multiple plane procedures that include the plane for data access, the plane for business, the database plane, and the plane for the user interface. The plane for the user interface is the structure of the database interface, while the plane for the business consists of the database that aids business protocols and procedures.
ETL stands for Extract, Transform and Load. It is a process where you copy data from various data sources to a particular data destination. ETL can be used for the following:
ETL testing is a data validation technique that allows data to move from one source to one data destination.
Database testing is the checking of your database to see that it is in order. This includes things such as schema, tables, and triggers – all under controlled conditions for accurate results. Another interesting fact about data testing is that it also provides checking of data consistency and integrity.
An application’s validity can be jeopardized, resulting in enormous financial losses that might bring the company to its knees. From more minor data attributes like the number of retweets on a tweet to the actual worth of assets on a trading platform, the intensity of these effects can vary greatly. There are some data thefts and integrity breaches that database testing cannot avoid, but the worst effects are minimized by examining the database system extensively.
We will discuss the difference between ETL testing and database testing in this section for better clarity.
|Function||Database Testing||ETL Testing|
|Main Goal||Data integration and validation||Extract, Transform and Load data for BI Reporting|
|System Applicable||A transactional system where business flow occurs||A system that contains historical data without being in a business flow environment|
|Common tools||Selenium, QTP, etc.||Informatica, QuerySurge, etc.|
|Business Need||It helps with multiple application data integrations.||It helps with information, analytical reporting, and forecasting.|
|Type of Database||It is normally used in OLTP systems||It is applied to OLAP systems|
|Type of Data||Normalized data comprising of more joins||De-normalized data comprise of fewer joins, more indexes, and aggregations.|
Overall, this article gives you a rundown of the fundamental differences between database testing and ETL testing to enable you to carry out your validation process successfully. Also, things to keep in mind when deciding how much testing you need to do in your areas of expertise and how to plan your testing system so that relevant aspects aren’t missed in the process.