In the previous post, we started by creating an Azure Data Factory, then we navigated to it. In this post, we will navigate inside the Azure Data Factory. Let’s look at the Azure Data Factory user interface and the four Azure Data Factory pages.
Azure Data Factory Pages
On the left side of the screen, you will see the main navigation menu. Click on the arrows to expand and collapse the menu:
Once we expand the navigation menu, we see that Azure Data Factory consists of four main pages: Data Factory, Author, Monitor, and Manage:
In Azure Data Factory, you can connect to a Git repository using either GitHub or Azure DevOps. When connecting, you have to specify which collaboration branch to use. In most cases, the default branch is used. Historically, the default branch name in git repositories has been “master“. This is problematic because it is not inclusive and is very offensive to many people.
The Git project, GitHub, and Azure DevOps are making changes to allow users to specify a different default branch name. GitHub and Azure DevOps will be changing their default branch names to “main” in 2020. I fully support this change and will be doing the same in my projects.
In this post, we will go through how to rename the default branch from “master” to “main” in Azure Data Factory Git repositories hosted in GitHub and Azure DevOps. Then we will reconnect Azure Data Factory and configure it to use the new “main” branch as the collaboration branch.
For these examples, I’m using my personal demo projects. I’m not taking into consideration any branch policies, other users, third-party tools, or external dependencies. As always, keep in mind that this is most likely a larger change, both technically and organizationally, in production and enterprise projects. 😊
The Short Version
Create a new “main” branch in your Git repository
Set the new “main” branch as the default branch in your Git repository
Delete the old “master” branch in your Git repository
Disconnect from your Git repository in Azure Data Factory
Reconnect to your Git repository in Azure Data Factory using the new “main” branch as the collaboration branch
NIC 2020 is a brand new event for me, both as an attendee and speaker. It takes place in Oslo Spektrum, one of Norway’s largest indoor arenas. When I hear Oslo Spektrum, I think of concerts, so I’m very excited to see what it’s like to attend a conference there! I really have no idea what to expect at this event, and that’s fun 🤓
NIC 2020 Schedule
NIC is short for Nordic Infrastructure Conference, so it’s not my typical data conference. However, I will do my best to make my session even more relevant to this audience. I want to add a few more slides about where Azure Data Factory fits into architectures and solutions, for example. I’ll do some brainstorming. Hmm. Challenge accepted!
On March 31st, I will be presenting my A Day Full of Azure Data Factory training day at SQLBits 2020. Yay! 🤓
SQLBits is one of my absolute favorite events. I was literally jumping up and down when I got the news that I was selected as a speaker! 🥳 In addition to presenting a training day session, I will present a general session, and volunteer again on the other days. Woohoo!
If you are considering registering for SQLBits 2020, I highly recommend that you make a decision and register as soon as possible. Why? Because the prices go up on January 11th! Early bird pricing is only £999 for two full-day training days and three conference days. That’s a bargain! From January 11th, the price goes up to £1199. From February 15th, the price goes up to £1499.
For the past 25 days, I have written one blog post per day about Azure Data Factory. My goal was to start completely from scratch and cover the fundamentals in casual, bite-sized blog posts. This became the Beginner’s Guide to Azure Data Factory. Today, I will share a bunch of resources to help you continue your own learning journey.
I’ve already seen from your questions and comments that you are ready to jump way ahead and dive into way more advanced topics than I ever intended this series to cover 😉 And as much as I love Azure Data Factory, I can’t cover everything. So a little further down, I will share where and how and from who you can continue learning about Azure Data Factory.