Data Warehouse Testing
Erroneous data affects your business more than you can imagine. Companies lose about 15% to 25% of their overall revenue to bad-quality data every year. Further, a study by LeadJen found that sales and marketing departments lose approximately 550 hours and as much as $32,000 per sales representative from using bad data.
Get DataQ's data warehouse testing solution for accurate and reliable data that saves you from the heavy consequences of poor quality data.
Data warehouse testing is a method in which the data inside a data warehouse is tested to ensure its reliability, accuracy, and consistency with the company’s data framework. Valid test cases are built and executed to identify data quality issues. With the increasing emphasis on data analytics to make significant business decisions, the need for data to be trustworthy cannot be stressed enough.
The process of data testing begins even before the data reaches the warehouse. Tests are inbuilt in the data pipeline itself, where the data undergoes extraction, transaction, and load (ETL) operations before they are deposited in the warehouse. Testing data at intermediate stages makes it possible to isolate and resolve inaccuracy early on.
Essentially, data warehouse testing combines data warehouse ETL testing and business intelligence testing (BI).