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Category: Source Control

Issues and Projects in GitHub

I have a new video:

In this video, we take a look at what GitHub has for project management, reviewing GitHub Projects and Issues.

The upshot is that GitHub has a fair amount of capability for project management. Its notion of Issues definitely feels fairly well fleshed out, which makes sense considering GitHub’s original purpose as a storehouse for open-source code repositories. By contrast, Projects are a relatively new feature and there’s still some room to grow there, especially if you’re used to project management tools like Jira or Trello.

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The Importance of Source Control for DBAs

Steve Jones explains that Git isn’t just for developers:

Git has become a fantastic tool for me, and many other technologists, over the last ten years. It’s almost ubiquitous in most of my clients, and so many people are comfortable with it. Many others aren’t, which is why I started a Git series for DBAs (and other Ops people) on my blog.

Quite a few people asked me why I recommend git over a file share for storing code that a team of Ops people or DBAs might use. Why isn’t a global file share a better choice in an organization? I think I have a few good reasons, but if you disagree, let me know in the discussion for this piece.

There are some annoyances around Git but good UI tools minimize a fair amount of the pain and the benefits are huge.

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The State of CI/CD in Power BI

Paul Turley violates Betteridge’s Law of Headlines:

The answer – finally – is a resounding YES! It has been a long road and the path to implementing Continuous Integration & Delivery (CI/CD) in all of its forms for Power BI is still a journey, but the capabilities are now a reality. This broad category includes a range of features and capabilities related to managing project files with version control and the ability to share and collaborate with other development team members. Additionally, we also have the ability to assign individual components of a solution to different team members who then check-out files and develop features, check them back in and merge changes into a feature branch. In enterprise-class projects, having these capabilities enables true Development Operations or DevOps: a process for managing iterative development, testing and deployment with automated builds, using a central process management tool. Implementing full-fledged DevOps is a big lift for most Business Intelligence professionals but the core concept of code version control is essential for any durable project.

Read on for Paul’s thoughts on the importance of source control and how you can pull this off.

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Basic Git for the DBA

Steve Jones provides a primer on Git:

One of the really interesting things over the last decade is both the rise of Git as the main VCS system for most projects, and the number of people who know nothing about it. Many of the latter seem intimidated, which is both interesting and strange to me. I usually think of technologies as ready to experiment, but I find more and more they only experiment in narrow boundaries.

This post outlines a quick way to get started with Git.

Click through to learn more.

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Version Control with Power BI and Microsoft Fabric

Reza Rad talks version control:

Power BI and Microsoft Fabric use Azure DevOps as the core component for their version and source control. The integration with Azure DevOps and Git helps maintain a copy of the source code and version it. It allows access to it anytime needed, plus the multi-development aspect added. In this article and video, you will learn how this integration works.

Click through for the article and video.

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Improving Performance of Power BI Project CI in Azure DevOps

Kevin Chant checks in a Power BI project:

I decided to test the guide with the Power BI report that I showed in my post about work with Microsoft Fabric Git integration and multiple workspaces.

So, I went through the guide and was pleasantly surprised that it showed how to do it with a YAML pipeline in Azure Pipelines. Which I must admit I prefer for reasons that I covered why in a previous post about disabling classic pipelines in Azure DevOps.

Read on for a review of the issues Kevin had to sort out, as well as two mechanisms to improve the performance of your Azure DevOps CI process.

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Pulling XMLA-Modified Power BI Datasets into Source Control

Marc Lelijveld has a fix:

Have you ever found yourself stuck with a modified Power BI dataset, thanks to those well-intentioned but troublesome changes you made through the XMLA endpoint? Does that sound familiar to you? What seemed like a convenient solution quickly turned into a frustrating challenge when you encountered the error message in the Power BI Service.

You wanted to seamlessly continue your development journey in Power BI Desktop, avoiding the need for a full data refresh or just quickly making that one small change, but now hitting a roadblock when trying to download PBIX file. The error message declared that your data model had been modified with the XMLA endpoint. But now, with Git integration you can overcome this challenge!

Read on to see how.

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Using DVC to Store Data Science Artifacts in Azure

I have a new video up:

In this video, we introduce DVC, a tool for version control management of data science and machine learning artifacts. We learn why Git isn’t the best place to store those large data files, how DVC integrates with Git, and how you can save your files in Azure Blob Storage.

Click through for the video, as well as a variety of links which helped me put it together.

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Where Git Repositories Store File Versions

Julia Evans digs into a folder:

Hello! I was talking to a friend about how git works today, and we got onto the topic – where does git store your files? We know that it’s in your .git directory, but where exactly in there are all the versions of your old files?

For example, this blog is in a git repository, and it contains a file called content/post/2019-06-28-brag-doc.markdown. Where is that in my .git folder? And where are the old versions of that file? Let’s investigate by writing some very short Python programs.

Read on to learn how you can parse it all out. And this is also reason number 3 why you don’t want to commit a large file to Git: even if you delete that file later, the contents will live in the .git folder forever, or at least until you take some manual action to excise it from Git’s history.

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