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Day: February 16, 2023

Visualizing Moving Averages in R with healthyR.ts

Steven Sanderson shows off a useful R library:

Are you interested in visualizing time series data in a clear and concise way? The R package {healthyR.ts} provides a variety of tools for time series analysis and visualization, including the ts_ma_plot() function.

The ts_ma_plot() function is designed to help you quickly and easily create moving average plots for time series data. This function takes several arguments, including the data you want to visualize, the date column from your data, the value column from your data, and the frequency of the aggregation.

Read on to learn more about this plot and see an example of it in action.

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Estimating Quantiles in Python

Christian Lorentzen digs into quantile calculation:

Applied statistics is dominated by the ubiquitous mean. For a change, this post is dedicated to quantiles. I will give my best to provide a good mix of theory and practical examples.

While the mean describes only the central tendency of a distribution or random sample, quantiles are able to describe the whole distribution. They appear in box-plots, in childrens’ weight-for-age curves, in salary survey results, in risk measures like the value-at-risk in the EU-wide solvency II framework for insurance companies, in quality control and in many more fields.

There are easy functions to calculate quantiles in R and Python; this post serves as a way of understanding the variety of quantile functions available and how they can affect results with small sample sizes.

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Azure Defender for SQL Overview

Deepthi Goguri looks at an Azure security offering:

Azure Defender for SQL, once you enable it will alert you for any SQL injection attacks, brute force attacks or any breached identities trying to access the data of your database. It also provides the vulnerability assessments. Vulnerability assessments give you alerts about the configurations of your database. If your database configuration is not following the standards of Azure, you will receive the alerts in the vulnerability assessment report.

You can enable the Azure Defender at the subscription level or at the Server level or at the resource level as well. Under the recommendations in the security center in the Azure portal, check for the Remediate security configuration. This will show if the Azure defender is configured properly.

I like Azure Defender for SQL, especially the advanced threat protection element. It’s based on IP address location and has caught me in different locations as I’ve traveled.

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Azure ML Overview

Sanil Mhatre gets us started with Azure Machine Learning:

The five-part series is designed to jump-start any IT professional’s journey in the fascinating world of Data Science with Azure Machine Learning (Azure ML). Readers don’t need prior knowledge of Data Science, Machine Learning, Statistics, or Azure to begin this adventure.

All you will need is an Azure subscription and I will show you how to get a free one that you can use to explore some of Azure’s features before I show you how to set up the Azure ML environment.

Part 1 is available now, with the other parts coming up soon. Even so, Part 1 is a big article on its own.

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Deploying a dacpac to the Serverless SQL Pool

Kevin Chant drops some dacpacs off at the (serverless) pool:

In this post I want to cover deploying a dacpac to a serverless SQL pool using Azure DevOps. Yes, you are reading that right. It is now possible thanks to a sqlpackage update.

To clarify, a dacpac file is a special file that you can use to deploy updates to SQL Server related databases using a state-based deployment. Plus, when I say serverless SQL pool I mean an Azure Synapse Analytics serverless SQL Pool.

Kevin includes examples for Azure DevOps as well as GitHub Actions.

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Power BI Dataset Scale-Out

Teo Lachev digs into a preview feature:

Microsoft announced a public preview of Power BI Dataset scale-out (DSO) for Power Premium, Premium per User (PPU), and Power BI Embedded. In the comments below the announcement, the article implies that this feature is a replacement for the Azure Analysis Services scale-out. “If you have an AAS scale out and you migrate your databases (aka models aka datasets aka cubes) to Power BI Premium, you get scale out automatically and at no extra cost.” Scaling out for free? Sure, where do I sign?

But then further down the comments, we have this clarification “[Power BI DSO happens] if a dataset is on peak load and the vcores of your capacity aren’t maxed out. Keep in mind that scalability on a single instance isn’t linear. By scaling out, we can achieve a better utilization of available CPU resources for high workloads. On the other hand, if your vcores are already maxed out, then scaling out brings no further perf benefit.” Confused? So was I, and I reached for clarification to Microsoft. Below, is my best understanding of what happens behind the scenes.

Click through for the answer.

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Security Updates for SQL Server 2014 and Up

Harvey Mora notes that Microsoft has been busy:

The Security Update for SQL Server 2022 RTM GDR is now available for download at the Microsoft Download Center and Microsoft Update Catalog sites. This package includes the new security fixes detailed in the KB Article.

This link is specifically for SQL Server 2022 but there are other posts for 2019, 2017, 2016, and 2014. This includes fixes to several security problems and is something you should install post-haste. Because this is a GDR, you’re also liable to find it in Windows Update if your update admins haven’t shut that channel off already.

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