Turn Your Quality Assurance from Cost to Investment

TestDriveā„¢ automates all types of testing for data integration applications for dramatically improved quality of applications as well as the data they produce.

TestDrive is a testing framework for your data and the processes behind them.

Flexible Testing Options

Offer a combination of various testing methods and approaches. Test a complete ETL/ELT process, validate your data by specifying acceptance criteria or validate ETL coding standards.

Automatic Testing Set-up, Execution, & Evaluation

Automatically archive existing data, prepare and deliver test data to the correct input locations. Test reports include comprehensive information from the top level statistics to detailed result comparisons.

Centralized Test Cases, Data Storage & Management

Store and access all information easily, using searchable fields to ensure highest user effectiveness

TestDrive improves the business decisions of major enterprise systems by affecting these areas:


  • Improving data quality
  • Reducing testing overhead
  • Integrating ETL tools
  • Increasing the value of every single test
  • Managing the testing repository

Agile Development With Confidence

Most enterprises today have adopted an agile development methodology in order to be more responsive to rapidly changing business requirements. In the absence of an automated testing tool, agile development can lead to more data quality problems. TestDrive supports agile development by making it easier and faster to execute tests. By doing more tests more frequently, you can quickly develop and test new applications while retaining confidence in the quality of your data.


Can you trust the data your IT department delivers?

How many different data integration and processing systems does your IT department rely on?

Your data strategy, marketing strategy, and even product strategy depends on that answer.

Do you understand how those numbers are calculated across your complete environment?

  • Where did they come from?
  • How were they calculated?
  • Are they up to date and reliable?
  • Who is responsible for those values?
  • Is the process of data integration transparent and traceable?


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