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In the part 18, we created a Cube based on the Azure Data Warehouse. In this new chapter, we will work with the cube, create backups and Finding the zone, working in the flow, these are the most efficient times for us, but they can be hard to find. Sometimes, a database will slow down exponentially when it is working hard, with many concurrent users. Well, to be more accurate, all the In his latest blog posts Brent shares his favourite research papers, explaining why he found them interesting and why you might too. STarting off with the Microsoft Research paper Plan Stitch: Harnessing the Best of Many Plans by Bailu Ding, Sudipto Das, Wentao Wu, Surajit As SQL developers, we tend to think of performance tuning in terms of crafting the best table indices, avoiding scalar and table valued functions, and an*lyzing query plans (among other things). But sometimes going back to the spec and applying some properties of elementary math can be the best way to begin to improve performance of SQL queries which implement mathematical formulas. This article is a case study of how I used this technique to optimize my SQL implementation of the Inverse Simpson Index. It seems like just a few weeks ago that I went over the 2018 results with Gene Kim. That was an exciting few weeks for me, running over the report in prep and then having the opportunity to host a webinar with Gene Kim. Exciting times, but it's been almost a year and the 2019 Kathi Kellenberger addresses the retirement of the Microsoft Professional Program in the latest SImple Talk Editorial. Stop by and Phil Factor demonstrates the correct use of the RETURN keyword in stored procedures or batches, to pas* back a non-zero RETURN code to the calling process, informing it of the error. He also explains some of its misuses. Achieving high availability is hard. Today Steve discusses the challenges of five nines of uptime. author Bill Pearson introduces the DAX MAX() and MAXX() functions, discussing similarities and differences. He then provides some