A Fine Slice Of SQL Server
Eitan Blumin wants to pump your passwords up:
This script generates various permutations and variations of common and weak passwords and uses the PWDCOMPARE function to check whether there are any enabled SQL logins that have these passwords.
Read on for several notions of what might constitute a weak password and notes on how to use this.
Comments closedKendra Little has a documentation change of note:
We now explicitly define ‘requests’ and ‘workers’ in the Azure SQL Database documentation, and we’ve cleaned up multiple places where we used to equate the two terms. In this post, I share the history of the two terms when it comes to Azure SQL Database, why the two were ever equated, and why things like this are tricky to change.
There’s a bit of behind-the-scenes around documentation work as well and the types of challenges you might run into when developing software for the public.
Comments closedSaveen Reddy has a few pointers for us:
Configure cost control and set daily, weekly or monthly Workspace Budget limits for serverless SQL pools. This easy-to-use management tool allows you to define and allocate your data assignment to ensure you never exceed your limits.
Click through for a post with animated GIFs for each tip.
Comments closedPaul Andrew continues a series on applying data mesh principles in Azure:
This principal is very broad, so I want to break down the theory vs practice as before. The idea of self-service is always a goal in any data platform and the normal thing for analytics is to focus on this within the context of our data consumption. Whereby a semantic layer technology can be used in a friendly business orientated, drag-drop type environment to create dashboards or whatever.
However, my interpretation of ‘self-serve’ for a data mesh architecture goes further than just the dashboard creation use case. This should not just apply at the data consumption layer, but all layers within the solution and for clarify, not just related to the data itself. Hence the term in this principal ‘data infrastructure as a platform’. This then unlocks the deeper implication of this serving for a data product, all abstracts of the platform can be consumed in a self-service manner from a series of predefined assets. Let’s think about this serving more like an internal marketplace or catalogue of assets for delivering everything the data product needs to enable a new node within the wider data mesh.
Read on for some deep thoughts on the topic.
Comments closedGilbert Quevauvilliers wants to see who’s using what tables:
I was reading through the blog post Announcing on-demand loading capabilities for large models in Power BI and I got a thought would it not be great to better understand which columns and tables are being used in my Power BI Premium/Premium per user datasets?
To do this, using the new DMV I could now look at the temperature of the tables-column.
The higher the temperature the more the table-column is being used in my reports!
Click through to see how Gilbert put this together but also pay attention to the caveats.
Comments closedSebastian Sauer has a tutorial for us:
A residual is defined as
ri=yi−Xi^βri=yi−Xiβ^.
That is, a residual is a tangible thing in the sense that it describes observables (cf. Gelman 2021, chap. 11.3, p. 161). That is, the residuals are the difference between observed and predicted values.
Read on for the concept of error terms and how we might plot them.
Comments closedPaul Randal continues a series on the transaction log:
In the first part of this series, I introduced basic terminology around logging, so I recommend you read that before continuing with this post. Everything else I’ll cover in the series requires knowing some of the architecture of the transaction log, so that’s what I’m going to discuss this time. Even if you’re not going to follow the series, some of the concepts I’m going to explain below are worth knowing for everyday tasks DBAs handle in production.
Read on to learn more about some key transaction log terminology.
Comments closedI highlight a pair of useful extensions for Visual Studio Code:
The first tool of choice is a big one, Yu Zhang’s Markdown All in One. This extension provides several great features. One of my favorites is its support for creating a table of contents. After opening the Command Palette (Ctrl + Shift + P), select
Markdown All In One: Create Table of Contentsand it creates a ToC for you based on the heading markers you already have.
Read on for several more things I like about this tool, as well as a discussion of a second useful extension.
Comments closedRichard Swinbank fights Visual Studio:
I sometimes find working with Visual Studio’s projects a challenge in multi-developer environments, because each project type seems to have its own vulnerability to Git merge conflicts. In the case of SSAS tabular, I’ve found two issues to be a regular source of conflicts:
Click through to see what those two causes are and what you can do to reduce the risk of having either one burn you.
Comments closedMarco Russo and Alberto Ferrari are linguists:
When calculation groups were introduced in 2019, we did not have a way to describe them in a textual form. A calculation group was represented as a table with one visible column and one or more rows, one for each calculated item. Each calculation item could have one or two DAX expressions associated with it – one for the calculation item itself and an optional one for the format string. Describing a calculation group in an article often required the writer to include screenshots of the Tabular Editor user interface, plus comments in the sample code to explain where each DAX expression should be placed in the user interface.
From the start we proposed a syntax to describe an entire calculation group in a textual form. However, there was no tool able to convert that syntax into the actual object in the Tabular model. For this reason, in the initial version of the articles about calculation groups we used a “pseudo-syntax” and we included comments that made the code more verbose and not necessarily easier to read. However, Tabular Editor 3 introduced the full DAX script syntax for calculation groups that we had hoped would be available in 2019. We decided to adopt that syntax in our content. We use this article as a guide to introduce and explain the DAX Script syntax for calculation groups.
Go check it out.
Comments closed