ETL vs DB Testing

Comprehensive testing of a data warehouse at every point throughout the ETL (extract, transform, load) process is becoming increasingly important as more data is being collected and used for strategic decision. ETL testing online training ia also available.

DB Testing versus ETL Testing

A large portion of us are minimal confounded over considering that both database testing and the ETL testing are comparative and same. The truth of the matter is they are comparative yet not same.

DB testing:

DB Testing is typically utilized broadly as a part of the business streams where there are different information streams happening in the application from numerous information sources on to a solitary table. The information source can be a table, level document, application or whatever else that can yield some yield information. Thus the yield information acquired can in any case be utilized as contribution for the consecutive business stream. Subsequently when we perform DB testing the most vital thing that must be caught is the way the information can get changed from the source alongside how it gets spared in the destination area.

Synchronization is one noteworthy and the vital thing that must be considered when playing out the DB testing. Because of the situating of the application in the design stream, there may be few issues with the information or DB synchronization. Thus while playing out the testing, this must be taken consideration as this can conquer the potential invalid deserts or bugs.

Case #1:

Venture "A" has incorporated engineering where specific application makes utilization of information from a few different heterogeneous information sources. Consequently the respectability of these information with the destination area must be done alongside the approvals for the accompanying:

Essential remote key approval

Segment values uprightness

Invalid qualities for any segments

What is ETL Testing?

ETL testing is a unique sort of testing that the customer needs to have it accomplished for their determining and examination of their business. This is generally utilized for the reporting purposes. Case in point if the customers need provides details regarding the clients who utilize or go for their item in view of the day they buy, they need to make utilization of the ETL reports.

Post investigation and reporting, this information is information warehoused to an information stockroom where the old verifiable business information must be moved.

This is a numerous level testing as the information from the source is changed into various situations before it achieves the last ordained area.

Illustration #2:

We will consider a gathering "A" doing retail client business through a shopping business sector where the client can buy any family things required for their everyday survival. Here every one of the clients going by are given a remarkable enrollment id with which they can pick up focuses each time they come to buy things from the shopping market. The controls gave by the gathering say that the focuses picked up lapse each year. What's more, contingent on their utilization, the participation can be either moved up to a higher evaluation part or minimized to a lower grade part relatively to the present evaluation. Following 5 years of shopping business sector foundation now administration is searching for scaling up their business alongside income.

Henceforth they required few business reports with the goal that they can advance their clients.

In database testing we play out the accompanying:

1) Validations on the objective tables which are made with sections with sensible estimations as depicted in the intelligent mapping sheet and the information steering archive.

2) Manipulations like Inserting, overhauling and erasure of the client information can be performed on the any end client POS application in a coordinated framework alongside the back end database so that the same changes are reflected at last framework.

3) DB testing needs to guarantee that there is no client information that has been misjudged or even truncated. This may prompt difficult issues like in right mapping of client information with their steadfastness

In ETL testing we check for the accompanying:

1) Assuming there are 100 clients in the source, you will check whether every one of these clients alongside their information from the 100 columns have been moved from the source framework to the objective. This is known as confirmation of Data culmination check.

2) Checking if the client information has been appropriately controlled and exhibited in the 100 lines. This is just called as confirmation of Data exactness check.

3) Reports for the clients who have picked up focuses more than x values inside the specific time frame.