Amid rapid growth in data complexity and technology advancement, many organizations still struggle to manage, understand, and measurably improve their legacy and evolving data ecosystems. In this hands-on data lab, you will learn how to build flexible data enrichment models, reusable tools and repeatable processes to 1) establish a constituent data integrity index/baseline 2) explore, visualize and measure constituent data integrity 3) identify and prioritize opportunities to improve your overall data quality in systematic and sustainable ways towards insights, equity and efficiency.

At our educational institutions, we use assessments and remediation for better student outcomes.
So, how can you improve your data outcomes?

In this session – we’ll cover how to leverage the data quality life cycle to improve your data.

By grading your data (on consistency, validation, and recency) and remediating the elements that aren’t passing the grade – you can ensure that every data outcome is "better".