Chicago Data Night – Dexter Horthy (Metalytics)

Please join us for our monthly Chicago Data Night, cohosted by ChiData and DSI. Practitioners, academics, and aficionados within the Chicago area are all invited to be part of a community at the intersection of industry and academia, brought together by a mutual interest in data. Each month, guest speakers will cover a specific data-related topic.

Hors d’oeuvres and drinks will be provided. Admission is free, and we strongly encourage filling out an RSVP here.

Agenda
5:00pm:   Doors Open
5:30pm:   Welcome Remarks
5:35pm:   Guest Speaker
6:30pm:   Q&A
6:45pm:   Reception

Meeting Location
The Auditorium at 1871
Merchandise Mart, #1212
222 W Merchandise Mart Plaza
Chicago, IL 60654

Abstract: With all the cool data tech out there for data modeling, observability, analytics, quality, contracts, BI, etc, it can be very easy to fall in love with a particular data stack and a particular solution. But the best *product* teams out there will remind you that you’ll get a lot more done if you “fall in love with the problem” rather than any particular solution. For both product teams and data teams, a big part of that means understanding your users, and specifically for data teams, understanding the value users get from data and data products. What decisions are they making with data? What does data enable them to do? What business outcomes does it drive?

On the other hand, the work to do all this discovery about what data is valuable and why can be difficult and tedious. Stakeholders are notoriously busy and tend to be a lot better at asking for “I need XYZ chart” vs. “I need to solve ABC problem”. Most teams are already buried in ad-hoc requests and big migration projects – how can they *also* find the time to deeply get to know their users and fall in love with the right problems?

In this talk we’ll discuss the grounding and motivations for product thinking in data, how to get started in applying these principles to your data projects, share success stories from top-notch teams like GitLab, Netlify, ZoomInfo, and others, and explore some open source tools and techniques that can help.