Collecting and methodizing data for decision making processes is crucial to the better operations of many businesses. The data if properly presented will have the ability to appraise earlier trends and display a real time data that gives you a competitive advantage.
If you discover software defect that is identified at a later stage of development the costs will rise too high. For data warehousing,an additional expense of using incorrect data is that wrong business decisions will be made. Set the proper testing goals to support early detection of software flaws. The following goals must be included for data warehouse software and ensure the following testing tasks.
Completeness of the data
The tester must check that the data loads in the warehouse completely. See that every field, record and complete content loads correctly to the database. Also there is a need to relate the record counts between the one that is loaded and the one from the source data. Then compare unique values in the key fields. This will support identifying a number of possible data errors.
Transformation of the data
For transformation testing select sample records and check the transformations manually. Use strategies that utilize combination of automated data movement verifications and automatic data profiling. The testers here will be required to have a thorough knowledge of ETL logic. So the combination testing is a better long-term strategy.
Quality of the data
A proper data warehouse testing is possible only with accurate rejects. The testing procedure also must be able to identify wrong data and substituted default values.
Flexibility of the data
As the volume of data increases the ETL also should be able to escalate its load. The competence of the queries must not drop with augmented loads. All the related and possible problems should be identified by the tester to maintain the flexibility of the software.
Integration Testing of the data
Integration testing checks software’s compatibility to all devices and applications. The difficulties may occur mostly through the incorrect suppositions about the application’s assembly;the integration test should make use of production-like data. Integration testing has to be executed like a joint effort from designing and developing team. This makes sure that you have good outcomes for softwares.