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Author: Kevin Feasel

Pre-Attentive Attributes and Visualization

Alex Velez hits on an important topic:

Have you ever wondered whether the graph or the slide you created is any good? Was the time you spent choosing colors, deleting gridlines, and wordsmithing slide titles, worth it, or for naught? While the answer is certainly more nuanced than a simple yes or no, there is a quick way to gain some insight into this: the where are your eyes drawn? test, also known as WAYED. It’s a simple question, but it can help to refine your own creations, and provides a construct for giving feedback to others.

Click through for the test and a bit more information about pre-attentive attributes.

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Data Exfiltration Protection and Synapse Pipelines

Luke Moloney shuts it down:

Before we discuss how DEP applies to Synapse Pipelines, it is important to level-set on some Synapse Pipelines specific concepts – if you are familiar with Synapse Pipelines or Azure Data Factory you can skip over this section and jump to Synapse Pipeline connectivity without DEP enabled.

For a more generalized introduction to Synapse Pipelines check out this doc article.

Synapse Pipelines enables users to connect to a range of different data services, through what is called a Linked Service. 

The big trick, using self-hosted integration runtimes, is something Luke spends a fair amount of time on.

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Physical and Logical Backups in MySQL

Lukas Vileikis continues a series on MySQL backups:

Everyone who has ever backed up data using any kind of RDBMS knows a thing or two about backups. Backups are a central part of data integrity – especially nowadays, when data breaches are happening left and right. Properly tested backups are crucial to any company: once something happens to our data, they help us quickly get back on track. However, some of you may have heard about the differences between backups in database management systems – backups are also classified into a couple of forms unique to themselves. We’re talking about the physical and logical forms – these have their own advantages and downsides: let’s explore those and the differences between the two. This tutorial is geared towards MySQL, but we will also provide some advice that is not exclusive to MySQL.

Click through to learn those differences.

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The Problem of Reproducability in Neural Networks

Pete Warden explains a problem:

Last week I had a question from a colleague about reproducibility in TensorFlow, specifically in the 1.14 era. He wanted to be able to run the same training code multiple times and get exactly the same results, which on the surface doesn’t seem like an unreasonable expectation. Machine learning training is fundamentally a series of arithmetic operations applied repeatedly, so what makes getting the same results every time so hard? I had the same question when we first started TensorFlow, and I was lucky enough to learn some of the answers from the numerical programming experts on the team, so I want to share a bit of what I discovered.

Read on for that answer.

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Where Extended Events Go by Default

Tom Zika is curious:

Have you ever wondered where the .xel file is saved when you create a new Extended Event session and don’t specify the full path (just the file name)?

Like so: [image removed because you should go to Tom’s site and see it, ed.]

Well, so did I and here’s what I’ve found out.

Click through to learn where these files end up if you don’t specify anything.

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SQL Server 2022 Query Store Hints

Matthew McGiffen takes a hint:

Another neat little feature in SQL Server 2022 is Query Store Hints. This is the ability to apply a query hint through Query Store rather than having to modify existing code or fiddle around with plan guides.


Query hints are a way to influence optimizer behaviour towards generating desired execution plans for a given query. The word “hint” is a bit of a misnomer as usually they mandate what you wish to happen.

Right. They’re ‘hints’ in the way that my wife ‘hints’ that I should take out the garbage.

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Controlling Cosmos DB Time to Live

Rahul Mehta pulls out the stopwatch:

As Microsoft states, Azure Cosmos DB “is a fully managed NoSQL database service for building scalable, high-performance applications”. Cosmos DB is widely used for storing NoSQL data with options to create using different Core (SQL), MongoDB, Cassandra, Table, and using gremlin.

With wide usage, the content storage also increases, sometimes even in Gigabytes a day. With such content storage, retention and archival of data are one of the common ask from the customer. Today, we are going to talk about how to retain data and remove unnecessary data periodically from Azure Cosmos DB. Before we do that, we need to understand a storage concept called “Container”

Read on to learn about containers, as well as the built-in way to garbage collect data.

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Azure Synapse Analytics Updates for November 2022

Ryan Majidimehr has a bundle of updates for us:

We are always working to improve Azure Analytics Spark performance. We are making significant changes that will increase Spark performance by up to 77%.  

Based on our testing using the 1TB TPC-H industry benchmark, you’re likely to see up to 77% increased performance. While your workload may perform differently than the TPC-H benchmark, everyone is expected to see improved performance. These Spark performance improvements come from moving to the latest Azure v5 VMs which have improved CPU performance, increased temporary SSD throughput, and lastly higher remote storage IOPS.  

Click through for a whole bunch of updates.

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Migrating Azure Analysis Services to Power BI Premium

Gilbert Quevauvilliers dumps AAS:

I thought it would be a good idea to walk through the steps when looking to migrate AAS to PBI.

In the past when I had to do this for clients it was a lot of manual steps and a lot of small things to get just right. This process is now seamless and awesome!

Reviewing Gilbert’s step-by-step process, yeah, this is easy, though watch out for the pitfalls Gilbert found.

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