Data is the backbone of any organization. Good data supports the business and helps ensure smart business decisions are made. Bad data, on the other hand… well, you don’t want bad data. But how do you make sure you have accurate and valid data? Data validation and testing are great places to start.
Data Testing vs. Data Validation
While they sound similar, data testing and data validation are both key to good data. Data testing takes small amounts of data and checks the expected results in a development or lab environment. Data validation, on the other hand, checks larger amounts of data in production environments. You can start small and work your way up to incorporating both processes into your database best practices. It might seem like a lot of work at first, but by implementing small changes now, you can avoid the usual reactive method and give your business the opportunity to stay ahead of issues.
Isolate small parts of your system for testing. Work with the database management team to set up a suitable lab environment with temporary datastores to test small subsets of data.
To make sure your data combines the way it’s supposed to, you can break down the intended data transformations into smaller pieces to test them in your lab environment. Be sure to track how your data moves between two points and ensure the transformation process is functioning properly.
Monitor Production Databases
It’s not over when your test environment shows your data is valid. Data validation is an ongoing process, and you should continue it in production environments. Continuing to validate your data will allow you to sort out any outdated information or data no longer relevant.
If you’re transferring data from one system to another, you should confirm it ends up where it’s meant to and hasn’t changed somewhere along the way. You can also use this process to verify data is optimized for your business needs and establish a plan for continuous database monitoring
Automate, Automate, Automate
It would take significant time and energy to do all this manually. Leverage automation to your advantage—standardization and repetition are your friends.
These steps may come with their own obstacles, but in the end, they’ll be worth it for your business. Bad data can affect companies no matter their size or industry, so understanding how and when to preform testing can help you validate your data and make the best possible decisions for the future. Remember to continue monitoring and validating your data even after initial testing for the best results.