Bad data is not actually the problem. The problem is when you *don’t know* if your data is bad.
If you want to improve trust in your data and your outputs, your goal should be eliminating uncertainty. Because if people don’t have trust in your data, they’ll be questioning the entire process and pipeline behind it.
Watch this webinar to learn how you can improve trust in your data by cultivating data quality in every step of your data’s lifecycle.
We’ll show you exactly where and how you should be putting measures in place to improve data quality and build trust, with recommendations for what to do at every stage of your process.
We'll cover:
- How to build trust by focusing on certainty and consistency
- Where data quality fits within the data lifecycle
- How power users, IT and end users can all collaborate on improving the quality of their outcomes
- Why measuring data quality isn’t always a good idea
- How CloverDX can help you build trust in your data
Calvin Cortez works with customers to introduce CloverDX, prototype rapid solutions to meet different use cases, and solve specific client data problems.
