Environmental Mapping and GIS

AI is changing how art is made. But when does it stop being your work and start being the machine’s? This month we're going to be doing a panel with with digital image, music, and written word artists, talking about at what point, while using AI in the creation process, does the work become not the artist creation? We encourage audience participation during this event that will be moderated by Chris Slee. Whether you’re deep in the field or just getting curious, come connect with others building and exploring AI in Columbus. Sponsored by [Transform Labs](https://www.transformlabs.com/services) Sign up also accessible via [Transform Labs Luma](https://luma.com/55umjqta)

Pay attention! We’re delaying a week for those of you who may be on Spring break and/or celebrating the holiday. Ok, no pancakes, but waffles-a-plenty. Join the local UX and Digital Design community for a casual monthly breakfast. Look for us upstairs!

We'll meet at Wyandot Park, cross Riverside Dr at Lane Rd, then walk south along the water to Griggs Park and back — 4.8 miles total. A scenic out-and-back route along the Scioto River. One of the nicer stretches of trail in Columbus. Parking is available at Wyandot Park, off Lane Rd. Here's an overview of the route on Google Maps: https://maps.app.goo.gl/uqweEoi6vcpY4esTA All paces welcome. See you there.

Join us for a two mile trail hike alongside the Brookside Trail at Blendon Woods Metro Park. This trail is largely gravel and does include some hills and stairs. Hopefully we will see some wildlife while hike this scenic trail! Join us!

The Fellowship of the Star Schema: Transforming OLTP Data for Power BI One does not simply build reports on OLTP data. Join us on an epic journey from the depths of raw, normalized tables to the shining halls of a well-modeled star schema fit for Power BI greatness. We will demystify the differences between OLTP and OLAP, walk through star schema vs snowflake (and why Power BI has a clear favorite), and show you the compression differences between normalized and columnar storage that will make you never look at an OLTP model the same way again. We will cover the different types of dimensions, when to use them, and how to handle Slowly Changing Dimensions without losing your mind. You will leave knowing exactly how to identify a bad model, how to convert OLTP data into a clean star schema, and how to forge relationships that rule them all. Whether you are a data wizard, a curious hobbit, or somewhere in between, your models will never be the same.