Hi! I’m Cathrine :) I really like Azure Data Factory. It’s one of my favorite topics, I can talk about it for hours. (And I do.) But talking about it can only help so many people – the ones who happen to attend an event where I’m presenting a session. So I’ve decided to try something new… I’m going to write an introduction to Azure Data Factory! And not just one blog post. A whole bunch of them.

I’m going to take all the things I like to talk about and turn them into bite-sized blog posts that you can read through at your own pace and reference later. I’ve named this series Beginner’s Guide to Azure Data Factory. You may not be new to ETL, data integration, Azure, or SQL, but we’re going to start completely from scratch when it comes to Azure Data Factory.

Does that sound good? Are you in? Cool. Let’s go!

In the introduction to Azure Data Factory, we learned a little bit about the history of Azure Data Factory and what you can use it for. In this post, we will be creating an Azure Data Factory and getting familiar with the user interface.

Spoiler alert! Creating an Azure Data Factory is a fairly quick click-click-click process, and you’re done. But! Before you can do that, you need an Azure Subscription, and the right permissions on that subscription. Let’s get that sorted out first.

Azure Subscription and Permissions

If you don’t already have an Azure Subscription, you can create a free account on azure.microsoft.com/free. (Woohoo! Free! Yay!) Some of the Azure services will always be free, while some are free for the first 12 months. You get $200 worth of credits that last 30 days so you can test and learn the paid Azure services. One tip: Time your free account wisely :)

If you already have an Azure subscription, make sure that you have the permissions you need. To create an Azure Data Factory, you need to either:

In the previous post, we started by creating an Azure Data Factory, then we looked at the user interface and the three main Azure Data Factory pages. In this post, we will go through the Author page in more detail. Let’s look at the different Azure Data Factory components!

Azure Data Factory Components

On the left side of the Author page, you will see your factory resources. In this example, we have already created one pipeline, two datasets, and one data flow:

Let’s go through each of these Azure Data Factory components and explain what they are and what they do.

In the previous post, we looked at the different Azure Data Factory components. In this post, we’re going to tie everything together and start making things happen. Woohoo! First, we will get familiar with our demo datasets. Then, we will create our Azure Storage Accounts that we will copy data into. Finally, we will start copying data using the Copy Data Wizard.

Demo Datasets

First, let’s get familiar with the demo datasets we will be using. I don’t know about you, but I’m a teeny tiny bit tired of the AdventureWorks demos. (I don’t even own a bike…) WideWorldImporters is at least a little more interesting. (Yay, IT joke mugs and chocolate frogs!) But! Let’s use something that’s not already in relational database format.

Let me present… *drumroll* 🥁

In the previous post, we used the Copy Data Wizard to copy a file from our demo dataset to our storage account. The Copy Data Wizard created all the factory resources for us: pipelines, activities, datasets, and linked services.

In this post, we will go through pipelines in more detail. How do we create and organize them? What are their main properties? Can we edit them without using the graphical user interface?

Pipelines: The Basics

When I was new to Azure Data Factory, I had many questions, but I didn’t always have someone to ask and learn from. When I did work in a team, I didn’t always dare ask my team members for help, because I felt silly for asking about things that I felt I should probably know.

Yeah, I know… It’s easy to tell others that there are no silly questions, but I don’t always listen to myself :)

I don’t want you to feel the same way! So. Let’s start from the beginning. These are the questions that I had when I was new to Azure Data Factory. Or, these are the questions that I realized I should have asked when I discovered something by accident and went “Oh! So that’s what that is! I wish I knew that last week!“