Creating test cases manually and sampling data row by row are not efficient or reliable methods for testing large datasets. Reduce manual effort and save time by automating data testing.
The use of continuous integration in development and constant change in data requires systematic testing and monitoring to detect errors and ensure data quality.
Poor data often means business reports are not reliable and additional development is required. We help you to detect errors in data before any significant negative impact or delays are caused.
Features and attributes
Data source comparisonCompare datasets from different data souces by comparing rows one-to-one using our built-in compare engine. This allows users to check millions of rows to find errors caused by problems in ETL. It is also possible to compare aggregated values from both sides to check for inequality.
Automated test creationAutomatically generate test cases using reusable dynamic rules. Generated tests are automatically changed in the background to be in accordance with datasource metadata. This means adding or removing columns from a view or table keeps the test case up to date and checks for errors in new columns. LiTech test generation engine allows users to generate tests in bulk to save time and reduce manual effort.
Supported data sourcesWe support a wide variety of commonly used database engines and technologies, such as:
- SQL Server
- SAP IQ
- SAP Hana
- RESTful API
- CSV files