Binary Options

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!

If you are interested in selecting investment choices for your 401(k) or other workplace savings plan, minimizing your income tax liability, or identifying the most effective investments for your brokerage account, we are the group for you. We are a local chapter of Bogleheads**®**, whose investment strategy can be found here: https://www.bogleheads.org/wiki/Bogleheads%C2%AE_investment_philosophy Or you can peruse the Boglehead forum here: https://www.bogleheads.org/index.php I look forward to seeing you there. Mark Vonder Haar

**Welcome to the Women’s Columbus Bogleheads® Sub-Group** This sub-group is for **women who want to learn and discuss finances in a safe, supportive space**. For those interested in moving towards financial independence and retirement by learning investment basics, choosing your 401(k) investments, minimizing taxes, and more. We’re a local chapter of **Bogleheads®**, following a long-term, practical investment philosophy: [Investment Philosophy](https://www.bogleheads.org/wiki/Bogleheads%C2%AE_investment_philosophy): https://www.bogleheads.org/wiki/Bogleheads%C2%AE_investment_philosophy [Bogleheads Forum](https://www.bogleheads.org/index.php): https://www.bogleheads.org/index.php No question is too small, and no experience is too simple. Share, ask, and learn — at your own pace, without judgment, in a group of like-minded women. Let’s build confidence and knowledge **together**!

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.