Weekly reading #28
September is over. This was not a good month for us. We had to cancel the conferences planned for September and were not able to write as much as we wanted to. We have a lot of great topics to share next weeks! Today – let’s start with some fresh information from the data platform world
Real-time moving averages for IoT with R
A very interesting article about the way you could calculate the moving averages from the data streams. It looks easy once you read the article.
Tuning SQL Server Reporting Services
Tim Radney explains main concepts of the SSRS – this is different type of server so it also has it’s own characteristics. You need to know how to approach to licensing, tuning, recovery etc.
The Curious Case of… why a minimally-logged operation doesn’t make a log backup smaller
Paul Randal has another great post from his curious case of series. This time he explains why you do not have smaller log backup after a minimally-logged operations. He comes with an idea that backup occurs right after such operation so think for a while what could happen if you try to restore a dabatabase after this.
Master Model: Creating Derivative Tabular Models
Derivative techniques for creating tabular master models – something I have had to work with recently! This article helped me a lot!
[Book] SQL Server 2019 Revealed: Including Big Data Clusters and Machine Learning
Bob Ward has just announced his new book! It will be available on December 20th! I already know what I want for Christmas.
By the way – do not forget to visit the Interviews page – there are 7 interviews as of now but much more to come!
Interview no. 1 – Uwe Ricken
Interview no. 2 – Andre Melancia
Interview no. 3 – Rob Farley
Interview no. 4 – Grant Fritchey
Interview no. 5 – Aaron Bertrand
Interview no. 6 – Greg Low
Interview no. 7 – Joe Sack
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