A Fine Slice Of SQL Server
Olivier Van Steenlandt busts out the YAML:
In previous blog posts, I explained how to automate the Database Project Build & Deployment process using Azure DevOps (Release) Pipelines. These blog posts focused on setting up as easily as possible using the Classic Editor.
In this blog post, I’m going through the steps of setting up a build pipeline using YAML.
Read on to learn why the YAML-based approach is the best option for ADO and how to build a pipeline.
Comments closedBruno Gabrielli doesn’t want a static cut-off:
In this new blog post I am going to explain how to use dynamic threshold in log alerts. Think for a second, that you need to create an alert that must, at the same time, apply to more than one resource and react to different thresholds.
The solution is inside the power of the Kusto Query Language or KQL.
Click through for examples.
Comments closedRichard Swinbank thinks about process:
In this series I’ll be talking a lot about workflow. Loosely speaking, report development workflow is the set of steps you have to take to create or update a Power BI report. This typically starts in Power BI desktop, and doesn’t end until users are able to get business value out of a report in the Power BI service.
A good workflow frees a report developer to do the things they like and are good at – understanding business problems, and crafting beautiful reports to help solve them. Anything that that doesn’t contribute to that just gets in the way – a bad workflow clutters up the development experience with peripheral tasks like version control, managing environments and performing deployments.
Richard shares a good number of thoughts on the matter, so check them out.
Comments closedSince Windows Server Update Services synchronizes the list of Windows Updates from the source Microsoft Servers on a regular basis, the history of sync events can become quite tedious to load in the User Interface. Frustratingly, there is no way through the user interface to remove old history for synchronization events. The SQL Server T-SQL code below creates a stored procedure that can be used to cleanup old events prior to a particular cut-off date. I run the code via a SQL Server Agent job daily, with a cut-off date of 30 days ago.
Click through for the stored procedure.
Comments closedRyan Booz helps a SQL Server DBA out:
Five years ago, I began my transition back to using PostgreSQL full-time, and it wasn’t the smoothest journey. One of the biggest reasons I struggled to make progress learning PostgreSQL early on was simply not knowing what I should be looking for. In fact, I often have conversations multiple times a month about the differences between SQL Server and PostgreSQL with folks setting out on a similar journey.
My guess is that you’re trying to figure out the same things, which is how you ended up on this series of posts.
Read on to take advantage of Ryan’s pain and suffering.
Comments closedA common use case with PostGIS data is to calculate things, such as distances between points, lengths of lines, and the area of polygons. The topic of accuracy, or inaccuracy, with
GEOMETRYdata comes up often. The most frequent offenders are generic SRIDs such as 3857 and 4326. In some projects accuracy is paramount. Non-negotiable. On the other hand, plenty of projects do not need accurate calculations. Those projects often rely on relationships between calculations, not the actual values of the calculations themselves. If Coffee shop Y is 4 times further away than Coffee shop Z. I’ll often go to Coffee shop Z just based on that.In most cases, users should still understand how significant the errors are. This post explores one approach to determine the how accurate (or not!) the calculations of a given SRID are in a particular region, based on latitude (North/South). The queries used in this post can be adjusted for your specific area.
Click through to see how much the choice of SRID can impact your results.
Comments closedPhil Seamark does some manufacturing analysis:
I always enjoy it when we get new DAX functions, especially so for the new set of WINDOW Functions recently added. As part of the April 2023 release of Power BI Desktop, we now have a RANK function and the ability to use a measure to control the order within the existing WINDOW function.
The first thing that sprung to my mind was to see how a Pareto calculation might leverage the new capability.
The basic idea of a Pareto calculation is to create a curve like representation of data ordered from largest to smallest.
Read on to see how.
2 CommentsChris Webb disables a visual element:
These numbers are counts of the number of rows for each value in the table that the field is from. The query to get these counts is usually quite fast and inexpensive, but if you’re filtering on a field from a very large table (for example a fact table) and/or using DirectQuery mode that might not be true. For example, the screenshot above is taken from a DirectQuery dataset and here’s the SQL query that generates the counts shown:
Read on to see how to do this.
Comments closedSteven Sanderson wants to spice things up:
The
styledtablepackage in R, which allows users to create styled tables in R Markdown documents. The package can help to create tables with various formatting options such as bold text, colored cells, and borders. It also has functionality on how to port these to Excel itself.The package offers a simple syntax that allows users to specify formatting options using HTML and CSS. The resulting table can be customized by changing the CSS file or by using the ‘styler’ function to apply custom styles to individual cells or rows.
Read on for more information on what the package does and a few examples of how it works.
Comments closedAmieroh Abrahams builds some graphs:
In Excel it is challenging to eye-ball which changes have been made to a graph, especially if these were minor changes. With R (and some easy to use version control systems), you can see exactly which files were changed. Also, in Excel, a user would usually draw a graph on a single Excel document, and if the same graph is required on a different data set, it is common to copy-and-paste a bunch of manipulations and configurations to another document. Such repeated human interaction is prone to introducing errors, as well as consuming a large amount of time. With R we can avoid this by creating functions, which can be used to run the same code on different data sets simply by changing the input, thereby producing reliable outputs and saving us a lot of time.
Click through for the article. One big thing in Excel’s defense that I did not see here was that it’s a lot easier to perform specific story-telling in Excel visuals. For example, highlight just these two data points, or annotate this segment of the visual. You can do those things in ggplot2 but it’s considerably more difficult than “right-click the data point and format.”
Comments closed