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Day: July 29, 2026

Improving Shiny and RMarkdown Inputs

Published 2026-07-29 by Kevin Feasel

Thomas Williams is back with more:

In my last post on improving inputs in R Markdown/Shiny, I covered four improvements to quality of life in interactive reports and dashboards. In this blog post I have three more, all approaches I’ve used to add professionalism to self-service R Markdown files.

In yet another plug for R Markdown: most of these techniques can be used in a single *.Rmd file, or can be included in many by putting them in a common CSS or javascript file and linking to it.

Click through to see what you can do.

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Database Refactoring with VS Code

Published 2026-07-29 by Kevin Feasel

Drew Skwiers-Koballa shows off some functionality:

SQL database projects are a fundamental tool for keeping your database in source control, tracking changes and collaborating on quickly evolving database needs. Not to be forgotten, their superpower is being able to dynamically generate deployment scripts that match the declared state and the exact environment you’re deploying to. SQL project development becomes more challenging when a database needs serious changes, where the requirements of the system have evolved to the point of having to rename tables and move objects between schemas.

This should be pretty familiar to people who have worked with various iterations of database projects in Visual Studio over the years.

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Huge Table Partitioning

Published 2026-07-29 by Kevin Feasel

Michael J. Swart partitions a rather large table:

Aaron Bertrand wants you to consider using partitioned tables and the sliding window pattern to help archive old data.

That’s a great idea. In fact, I’d like to do that at my own job. I have a truly humungous log table (Terabytes) and its clustered index is already on CreatedDate so it’s a good candidate for this pattern.

Click through to see how, but also one pain point you’re likely to run into when adding partitioning to existing large tables.

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A Primer on Indexing in SQL Server

Published 2026-07-29 by Kevin Feasel

Ed Pollack has a guide:

Indexes are supposed to make SQL Server faster – so why do so many databases end up slower, bloated, and harder to maintain when they have more of them? It usually comes down to misapplied indexes rather than missing ones. There may be too many that are too wide, tuned with settings that don’t fit the workload, or built on assumptions that stopped being true years ago.

This guide walks through the most common SQL Server index tuning mistakes seen in production environments, such as over-indexing, oversized INCLUDE lists, unnecessary fill factor settings, misuse of SORT_IN_TEMPDB, over-aggressive index maintenance – and the myth that heaps are a shortcut to speed. Features real examples.

I think this serves as a reasonable overview of the topic. You can certainly get into more nuance on a number of the topics, but this is a good starting point.

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The Performance Impact of Visual Calculations

Published 2026-07-29 by Kevin Feasel

Marco Russo and Alberto Ferrari dig into the nuance:

The goal of visual calculations is to simplify some reports and calculations, rather than to optimize performance. However, it is common sense that – in some scenarios – visual calculations can bring some benefit from the performance point of view.

The main idea is that a report may precompute some values and then, to further elaborate on them, it may use the content of the virtual table rather than recompute the values multiple times.

Read on to learn how you can adjudge what that visual calculation is doing for you in terms of performance relative to alternatives. But hey, if you’re stuck with Power BI Report Server, you don’t have to worry about visual calculations potentially slowing anything down. Mostly because you don’t get visual calculations.

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