We're all familiar with errors in our data, it's a constant battle to ensure data is clean and ready to be used. What many people may not realize is that there are many different ways that data can be improperly generated, transmitted, and stored. This presentation will discuss the generally recognized 6 dimensions of data quality, and discuss some examples from common instances where data can go wrong. We'll also share some real world examples of why clean data across all these dimension is important, not just for submitting data for a Statewide Data Warehouse, but for locally produced reports and dashboards.
