SQL Spot – Part 1


SQL Spot – Part 1


It has been going fast in 2016 for Microsoft BI. If we continue to move on like this, we’re in for a treat in 2017. However, more technical growth means more ground to cover and more knowledge to be gathered. In this blog series I want to share some interesting articles, which crossed my path in the past month, either professionally or out of personal interest. You can expect information ranging from business perspective to technical insights on various topics like SQL Server News, business perspectives, Power BI, SQL Server BI stack, features, data science, accidental DBA stuff and interesting learning or study materials. All rights go out the great blogging community.

I am mainly a BI developer being an accidental DBA sometimes. I like to pick up on the basics of things to help me out in occasions I’m forced to pick up the role. Also, with SP1 a lot of new features became available on standard editions as well. So, it is a good idea to have some of the enterprise’s feature fundamentals well understood. This month I tried to gather some highlights regarding SQL Server 2016 features or news you might have missed out on.

Business, releases and news


Power BI





  • SSAS Tabular v.next promises even more great new features such as the integration of the M language. Find out more here.
  • Azure SSAS , why and when is it interesting for you. Kasper does a great job of summing them it up here.
  • How to document your tabular or Power BI models.
  • The appraised cross directional filtering has made its way to the SQL Server 2016 SSAS tabular mode.
  • There are a lot of new functions for DAX, but I think the variables feature is really interesting in SQL Server 2016.
  • Have Marco Russo help you out with monitoring your tabular and multidimensional models with SSAS Events Analyzer.
  • SSAS Activity Monitor is an open source tool to monitor the current activity (sessions, transactions, connections, and locks) on an Analysis Services instance. It works for both Tabular and Multidimensional mode.




Data science










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