A Fine Slice Of SQL Server
I would like to illustrate a way which omitted variables interfere in logistic regression inference (or coefficient estimation). These effects are different than what is seen in linear regression, and possibly different than some expectations or intuitions.
This is an interesting article and there’s a really good comment helping to explain this effect in epidemiology.
Comments closedSteven Sanderson builds up a box plot:
Are you ready to dive into the world of data visualization in R? One powerful tool at your disposal is the box plot, also known as a box-and-whisker plot. This versatile chart can help you understand the distribution of your data and identify potential outliers. In this blog post, we’ll walk you through the process of creating box plots using R’s
ggplot2package, using theairqualitydataset as an example. Whether you’re a beginner or an experienced R programmer, you’ll find something valuable here.
Click through to learn what kind of information a box plot can provide, as well as how to create one using a variety of R libraries.
Comments closedAdrian Tam continues a series on core data types in R:
Vectors in R are supposed to be of homogeneous data type. You can use a list as the container if there are mixed data types, such as numbers and strings. The list and data frame are closely related in R. The data frame is probably more useful because it reflects how we usually collect statistics. In this post, you will learn about them. Specifically, you will know:
- What are lists and data frames in R
- How to manipulate lists and data frames
Read on to learn more about these two sorts of collections.
Comments closedWith a rising prices of utilities like gas and power and winter still being in progress it might be good to check your usage from time to time. With electricity and TOU meters, it is easy, retailer does that for you and you can check your consumption and projected bill at any time with a granularity of 30 minute interval (sometimes even less).
With gas (and water) it is trickier, those are being read manually every 2 – 3 months so you may be up for a surprise when the bill arrives.
I had a co-worker who tracked this stuff in meticulous detail over a period of several years, to the point where he knew exactly how much propane to buy in August (when prices are lowest) to get through winter with minimum waste.
Comments closedJose Manuel Jurado Diaz explains the difference:
Several days ago, I got a service request where we had a conversation about the differences about SQL Server Events: Attention Signal and User Error Message. In the realm of SQL Server, a well-rounded understanding of various events is crucial for optimizing performance, troubleshooting issues, and maintaining a robust database environment. In this article, we’ll delve into three important events: “Attention Signal,” “User Error Message,” and “Command Timeout.” We’ll explore their significance, scenarios where they occur, and provide a practical script to simulate and capture these events. Let’s dive in!
Read on to understand the intent of each of these event types.
Comments closedMeagan Longoria runs into a problem:
I have a client who was upgrading some servers from pre-2022 versions of SQL Server to SQL Server 2022 CU7. They had some multidimensional SSAS cubes that were to go on the new server. But they ran into an issue after the upgrade. After restoring a backup of an SSAS database to the new server they found that they could no longer modify the data source using SSMS.
Read on to see what the problem was, as well as how to fix it.
Comments closedA common requirement from Power BI customers in highly-regulated industries is the need to log users out of Power BI if they have been inactive for a certain amount of time. If your Power BI reports contain extremely sensitive data you don’t want someone to open a report, leave their desk for lunch, forget to lock their PC and let everyone in the office see what’s on their screen, for obvious reasons. This has actually been possible for some time now with Power BI and is now supported for Fabic, so I thought I’d write a blog post to raise awareness.
Read on to see how it works.
Comments closedAdrian Tam shows off one of the building blocks for R:
R is a language for programming with data. Unlike many other languages, the primitive data types in R are not scalars but vectors. Therefore, understanding how to deal with vectors is crucial to programming or reading the R code. In this post, you will learn about various vector operations in R. Specifically, you will know:
- What are the fundamental data objects in R
- How to work with vectors in R
This is often a little tricky for newcomers to the language to pick up, though if you’re already familiar with set-based operations in SQL, vector-based operations are fairly straightforward.
Comments closedAmieroh Abrahams cleans up some data:
As data scientists, we often find ourselves immersed in a vast sea of data, trying to extract valuable insights and hidden patterns. However, before we embark on the journey of data analysis and modeling, we must first navigate the crucial steps of data cleaning and preprocessing. In this blog post, we will explore the significance of data cleaning and preprocessing in data science workflows and provide practical tips and techniques to handle missing data, outliers, and data inconsistencies effectively.
Read on for several tactics which can help you clean up your data.
Comments closedJohnny Winter shares some advice:
With Fabric being a unified platform, the worlds of Power BI Developer and Data Engineer collide. So is a solid naming convention a good idea?
At Advancing Analytics, we say yes.
In fact, given the breadth of the platform and the variety of artifacts available for use in Fabric, it becomes even more important to have a strategy to be able to organise these items and make them quick and easy to identify.
Read on to see what Johnny recommends.
Comments closed