You don't need perfect data

While yesterday I wrote about prioritising data quality projects, I think it’s important to note that while for many of us the quality does need to be improved, we don’t need to be aiming for perfect.

What’s more important is that the expectations around the data have been set and you know those expectations will be met. That’s what allows you to build on it with confidence.

The data could be more complete, it could be more timely, it could have fewer duplicates, but as long as you know those limitations you can probably make good use of it.

Or if it doesn’t meet your requirements, you know what you need to ask for and can build the business case to improve the quality of the data.