Many organizations have databases without well-defined company entities. Their data may have originated from a legacy system that did not assign and govern company records, or perhaps it is due to the natural struggle to maintain company records amidst a mob of users wreaking havoc. Correcting this issue with manual effort is often impossible given the scope of datasets. Add to this the complexity of parent/subsidiary company relationships and you’ve got yourself quite a headache!

This session will explore the utilization of an advanced data matching algorithm to address this problem and yield cleanly identified and labeled company entities. We will be doing a deep dive into an association’s dataset and follow one data scientist’s problem solving journey from beginning to end.

Attendees will:

• Learn about automated solutions for data matching

• Learn about master data and why it’s important

• Gain problem solving insight from a deep dive into a complex problem

Duncan Bell is Vice President of Data Services at Association TRENDS, a publisher serving the association and nonprofit community with data, content, training and events. Duncan has been working in data for 9 years and is passionate about the power of automation to improve operational efficiency and fidelity of business outcomes. Duncan is the lead developer and architect for Bumblebee, Association TRENDS’s automated data cleanup solution for membership datasets.