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Movie Night - You, Me & Tuscany
Movie Night - You, Me & Tuscany
. 🎬 Movie Night You, Me & Tuscany Join us for a cinematic escape to the sun-drenched vineyards and romantic landscapes of Italy as we gather to watch You, Me & Tuscany, the new feel-good romantic comedy starring Halle Bailey and Regé‑Jean Page. Set against the breathtaking beauty of Tuscany, the film follows a spirited young woman whose impulsive decision to stay in a Tuscan villa leads to unexpected adventure, heartfelt moments, and a romance she never saw coming. Expect an evening filled with: 🍿 A beautiful cinematic escape to Italy 🍷 Relaxed social vibes and great conversation ✨ A feel-good romantic story perfect for movie lovers Whether you’re a fan of romantic comedies, stunning travel settings, or simply enjoy experiencing great films with great people, this will be a perfect night to unwind and connect. Come ready to relax, laugh, and be transported to Tuscany for the evening. Follow Black Love & Friends on [Facebook](https://www.facebook.com/share/17oXQtZz36/) and [Instagram](https://www.instagram.com/blackloveandfriends?igsh=djVrYnhqeG5nMjBx) to stay connected and be the first to hear about upcoming dimnets, social gatherings, and other exciting member-only events.
Support Rumours (Public event)
Support Rumours (Public event)
Imposter Syndrome by Kathy Wang
Imposter Syndrome by Kathy Wang
Semi in honor of March being International Women's Month Columbus libraries: [https://cml.bibliocommons.com/v2/record/S105C3454709](https://cml.bibliocommons.com/v2/record/S105C3454709) Location: SOW Plated Menu: [https://www.sowplated.com/menu-brunch/](https://www.sowplated.com/menu-brunch/) Book summary: In 2006 Julia Lerner is living in Moscow, a recent university graduate in computer science, when she's recruited by Russia's largest intelligence agency. By 2018 she's in Silicon Valley as COO of Tangerine, one of America's most famous technology companies. In between her executive management (make offers to promising startups, crush them and copy their features if they refuse); self promotion (check out her latest op-ed in the WSJ, on Work/Life Balance 2.0); and work in gender equality (transfer the most annoying females from her team), she funnels intelligence back to the motherland. But now Russia's asking for more, and Julia's getting nervous. Alice Lu is a first generation Chinese American whose parents are delighted she's working at Tangerine (such a successful company!). Too bad she's slogging away in the lower echelons, recently dumped, and now sharing her expensive two-bedroom apartment with her cousin Cheri, a perennial "founder's girlfriend". One afternoon, while performing a server check, Alice discovers some unusual activity, and now she's burdened with two powerful but distressing suspicions: Tangerine's privacy settings aren't as rigorous as the company claims they are, and the person abusing this loophole might be Julia Lerner herself. The closer Alice gets to Julia, the more Julia questions her own loyalties. Russia may have placed her in the Valley, but she's the one who built her career; isn't she entitled to protect the lifestyle she's earned?
CBusData: The Fellowship of the Star Schema: Transforming OLTP Data for Power BI
CBusData: The Fellowship of the Star Schema: Transforming OLTP Data for Power BI
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.