A Fine Slice Of SQL Server
Steven Sanderson achieves normality:
In data analysis, especially when dealing with multiple samples or distributions, ensuring comparability and removing biases is crucial. One powerful technique for achieving this is quantile normalization. This method aligns the distributions of values across different samples, making them more similar in terms of their statistical properties.
Read on to see how you can use the TidyDensity package to pull this off.
Leave a CommentMicrosoft has released a new learning path yesterday, Build AI Apps with Azure Database for PostgreSQL. I had the good fortune to write two of these modules:
Click through for direct links for the two modules. The way we wrote these, you can do the modules in any order and they’re self-contained, so you can pick and choose which ones you’d like to do.
Leave a CommentMeagan Longoria solves a problem:
Have you ever wanted to filter a visual by selecting a range of values for a measure? You may have found that you cannot populate a slicer with a measure. But you can do this another way.
I have a report that shows project expenses and budgets. I want users to be able to filter the list of project to only those which have expenses within my selected range. I also have 2 other slicers for project budget and percent of budget used, but let’s just focus on the expense amount slicer.
Read on to see how.
Leave a CommentI talked about Microsoft Fabric shortcuts in my blog post Microsoft Fabric – the great unifier (where I have updated the picture with the newest supported sources) and wanted to provide more details on how shortcuts work and reduce some confusion.
Read on for James’s key takeaways and notes on shortcuts.
Leave a CommentRobert Haas talks about a development challenge:
Hacking on PostgreSQL is really hard. I think a lot of people would agree with this statement, not all for the same reasons. Some might point to the character of discourse on the mailing list, others to the shortage of patch reviewers, and others still to the difficulty of getting the attention of a committer, or of feeling like a hostage to some committer’s whimsy. All of these are problems, but today I want to focus on the purely technical aspect of the problem: the extreme difficulty of writing reasonably correct patches.
Read on for Robert’s experience developing incremental backups in Postgres. In fairness, I think this is true of any complex system which becomes mission-critical. It’s really easy to develop in low-risk, limited-code, greenfield environments. As you change each of those properties, development gets considerably more challenging, even if people are doing the right things the right way and checking ego at the door.
Leave a CommentQuestion: How can I export all the SQL Agent Jobs in one action , rather than saving each one individually .
Read on for one fairly easy way to do it using SSMS.
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