Top Tips for Spring Cleaning in Eloqua

If you are reading this right now, you probably have some dirty data lying around in your databases.

But what is dirty data? It can mean different things for different people, but ultimately it’s data that is not normalized or standardized (i.e. storing variations of “United States” and “United States of America” for country in your database). Dirty data can also be data that is incomplete or outdated, caught up in conflicting data priorities, or data from an untrusted or unverified source. Why is this a problem? It makes your datasets difficult to segment and report, can lead to a ton of lead scoring issues, and even cause compliance and legal issues.