Powerboating

We meet at lunch each week and each meeting follows a fairly organized agenda. First all participants pass their business cards around. Then each member and guest is invited to give a one-minute overview of their company and what is a perfect referral for the week. We always have a 10 minute presentation from one of the members about their business in more detail. And finally we pass referrals. You're welcome to visit. Nobody is ever put on the spot. Bring plenty of cards!

**We'll have two meetings covering AI - this second one is for Positron** We will review which AI features are linked in for Positron, and how to use them. **Location:** The meetup will be at SPARK's ([https://annarborusa.org/](https://annarborusa.org/)) Ann Arbor site: [SPARK HQ (Ann Arbor)](https://urldefense.com/v3/__https://www.google.com/maps/place/Ann*Arbor*SPARK*Headquarters/@42.2792515,-83.7447708,17z/data=!3m1!4b1!4m5!3m4!1s0x883cae3effe193cb:0x5296a53db2a282bf!8m2!3d42.2792515!4d-83.7447708?hl=en-US__;Kysr!!HXCxUKc!3EEdBNXRJKknP6LCGkZetSuEsdtChFojQnOVitFUC5C0fyilqXEbiMstT9ajBR3Cw-55qoFkrElCjQvjMdTxUw$). There is on street parking, and parking at local structures. **This will be a hybrid meeting - the Zoom session starts at 6:30 PM.** **Time:** The doors will be open at 6:00, with pizza and beverages provided. We will have a meet-and-greet-and-pizza session, and then at 6:30 we'll have a presentation. **Zoom information:** https://us06web.zoom.us/j/86862937929?pwd=woa95D1r85dobjqxQ07NfBLNdTa9hc.1 Passcode: 705462 **If you can't get in, please call me at: 734 223-3307** **Document source:**

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.