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.

Most Prospect Management models rely on the gift cycle to categorize prospects. But is this the most accurate way to describe a prospect's philanthropic engagement with the institution? Does a prospect being cultivated for their first major gift really fall in the same category as a seasoned donor being cultivated for their 10th? The Prospect Development Team at Temple University decided to reframe the way they code and report on prospects based on simple measurements on the donors' records. This enabled the team to engage with the fundraisers they partner with to uncover new opportunities and allowed fundraisers to approach their portfolios in a more strategic way.