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Month: August 2023

Creating a Box Plot in R

Steven 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 ggplot2 package, using the airquality dataset 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.

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Lists and DataFrames in R

Adrian 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.

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Projecting Gas Bills with Excel

Jiri D. performs an estimate:

With 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.

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SQL Server Events: Attention Signal and User Error Message

Jose 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.

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Restoring SSAS Cubes to SQL Server 2022 CU5

Meagan 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.

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Idle Timeouts and Power BI

Chris Webb logs us all out:

A 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.

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A Primer on Vectors in R

Adrian 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.

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Data Pre-Processing in R

Amieroh 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.

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Naming Artifacts in Microsoft Fabric

Johnny 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.

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Private Endpoints and Azure SQL Managed Instance

Zoran Rilak begins a new series:

Last week we announced the general availability (GA) of private endpoints for Azure SQL Managed Instance. Today, we bring you examples of private endpoints in practical scenarios, starting from the basics and building to the more complex ones to follow in the second installment of this mini-series.

In this post, we’ll cover the following scenarios:

  1. Accessing SQL MI from another virtual network
  2. A more secure kind of public access
  3. Accessing SQL MI from your premises
  4. Making SQL MI available to managed Azure services

Click through to see these four scenarios at the architecture diagram level.

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