Purses

Join us for lunch at Cooper’s Hawk in Easton. If the weather is nice, we’ll enjoy lunch on their gorgeous patio!

The aim of this group is to get together and practice our German. Doesn’t matter if are a beginner or a native speaker. The goal is to speak and improve our German. Everyone is welcome! If the weather is good, look for us in the Biergarten. Pro Tip: Get there before 6:00 for happy hour pricing.

Meet at Wolfe Park parking lot by tennis courts. We willl walk along Alum Creek trail, through Jeffrey Mansion Park then along Bexley neighborhood and back. Optional lunch at Trolley District.

**Our April novel is: *The Hong Kong Widow* by Kristen Loesch** **This month’s novel blends gothic atmosphere with historical fiction and chilling horror, set against the haunting backdrop of China. The book is 368 pages in print and 10 hours and 42 minutes on audiobook.** In 1950s Hong Kong, Mei is a young refugee of the Chinese Communist revolution struggling to put her past in Shanghai behind her. When she receives a shocking invitation—to take part in a competition in one of the city's most notorious haunted houses, pitting six spirit mediums against one another in a series of six séances over six nights, until a single winner emerges—she has every reason to refuse. Except that the hostess, a former Shanghainese silent film star, is none other than the wife of the man who once destroyed Mei’s entire life. It is promised the winner will receive a fortune, but there is only one prize Mei wants: revenge. Decades later, the final night of that competition has become an infamous urban legend: The police were called to the scene of a brutal massacre but found no evidence, dismissing it as a collective hallucination. Mei knows what she saw, but now someone else is convinced they know what she did. She must uncover the truth about the last night she ever spent in that house—even if the ghosts of her past are waiting for her there. . . .

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.