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Day: November 12, 2019

High-Value Software Testing

Published 2019-11-12 by Kevin Feasel

RJ Zaworski has some principles around high-value testing:

Whatever the tools and approach, software testing proves that software does what it claims to do. Tests help developers eliminate defects, build confidence, practice good design, and ideally all three. They also take time to write, run, and update–time that’s no longer available for other development tasks.

High-value testing seeks to maximize the return on that investment. Like much of software development, it’s as much art as science. But a few practical principles can help keep things pointed in the right direction.

There’s a lot of good advice in this post.

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Thoughts on Large Datasets in Power BI

Published 2019-11-12 by Kevin Feasel

Teo Lachev has some early thoughts on large datasets in Power BI:

At Ignite 2019 Microsoft announced the public preview of large datasets in Power BI Premium. This is a significant milestone as now datasets can grow up to the capacity’s maximum memory (previously, the max size was 10 GB with P3 plan), thus opening the possibility of deploying organizational semantic models to Power BI. I consider this feature mostly suitable for organizational BI as I don’t imagine business users dealing with such large data volumes. I tested large datasets during its private preview, and I’d like to share some notes.

Teo has some open questions, and I’d like to see this shifted down to SSAS too.

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Powershell Notebooks in Azure Data Studio

Published 2019-11-12 by Kevin Feasel

Aaron Nelson announces a new feature in Azure Data Studio:

In order to get all the nice intellisense and tab completion features of the PowerShell language inside your PowerShell Notebooks, be sure to install the PowerShell extension from the Azure Data Studio marketplace.

At this point, the biggest remaining language is R, though I’d love to see F# support as well (hey, Azure Notebooks offers F# support).

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High Availability Announcements from Microsoft

Published 2019-11-12 by Kevin Feasel

Allan Hirt looks at a couple announcements from Microsoft:

I’m going to discuss what I feel are the biggest game changers. I knew licensing was changing as I had conversations with Microsoft around this months ago. I was not sure what the final result was going to be, but I’m fairly pleased. Is it perfect? No, but it’s much better than it was.

You’ll definitely want to read Allan’s thoughts on Microsoft’s SQL Server licensing changes, as well as a private preview of Azure Shared Disks.

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Errors with SQL Server TDE and Azure Key Vault

Published 2019-11-12 by Kevin Feasel

Amit Banerjee takes us through troubleshooting issues when using Azure Key Vault as the key storage mechanism for Transparent Data Encryption:

The first one was a 404 error. When I looked the application event log, I saw the following error:

Operation: getKeyByName
Key Name: ContosoRSAKey0
Message: [error:112, info:404, state:0] The server responded 404, because the key name was not found. Please make sure the key name exists in your vault.

The simple reason for the above error is that I was using an incorrect key name or the key didn’t exist in my Azure Key Vault. So the remediation is to check if the key exists in your Azure Key Vault. If not, then create the key.

Read on for additional errors you might run into, as well as a link to an Azure Data Studio notebook to set this up yourself.

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Notes on Wrangling Data Flows

Published 2019-11-12 by Kevin Feasel

Rayis Imayev calculates distance between two geographical points in an Azure Data Factory Wrangling data flow:

Brian Donovan and Dan Work from the University of Illinois has pointed out that this dataset “contains a large number of errors. For example, there are several trips where the reported meter distances are significantly shorter than the straight-line distance, violating Euclidean geometry“. So, that triggered my interest to add an additional column to this dataset with a straight line distance between two geo-points of pickup and dropoff locations, and that’s where I wanted Wrangling Data Flows to help me.

Read on for Rayis’s demonstration, as well as a long list of observations (positive and negative) about the current state of Wrangling data flows.

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