I’m a data geek 🤓 In fact, I like data so much that I have made it my career! I work with Azure Data and the Microsoft Data Platform, focusing on Data Integration using Azure Data Factory (ADF), Azure Synapse Analytics, and SQL Server Integration Services (SSIS).
In this category, I write technical posts and guides, and share my experiences with certification exams. You can also find a few interviews with Azure and SQL Server experts!
Azure Data posts may cover topics like Azure Data Factory, Azure Synapse Analytics, Azure SQL Databases, and Azure Data Lake Storage. Microsoft Data Platform posts may cover topics like SQL Server, T-SQL, and SQL Server Management Studio (SSMS), and SQL Server Integration Services (SSIS).
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 navigating to it.
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 ⏳
Hi! I’m Cathrine 👋🏻 I really like Azure Data Factory. It’s one of my favorite topics, I can talk about it for hours. 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.
Important: Exam DP-201 is retired as of August 31st, 2021. It has been replaced by Exam DP-203. You may still find the content in this post relevant, but I have not updated it for Exam DP-203.
Important: Exam DP-200 is retired as of August 31st, 2021. It has been replaced by Exam DP-203. You may still find the content in this post relevant, but I have not updated it for Exam DP-203.
Please note: Since I wrote this post, Wrangling Data Flows have been renamed to Power Queries, and there have been many updates in Azure Data Factory. I'm keeping this post as-is, please make sure you also read the official documentation.
In 2019, the Azure Data Factory team announced two exciting features. The first was Mapping Data Flows (currently in Public Preview), and the second was Wrangling Data Flows (currently in Limited Private Preview). Since then, I have heard many questions. One of the more common questions is “which should I use?” In this blog post, we will be comparing Mapping and Wrangling Data Flows to hopefully make it a little easier for you to answer that question.
Should you use Mapping or Wrangling Data Flows?
Now, we all know that the consultant answer to “which should I use?” is It Depends ™ 😄 But what does it depend on?
To me, it boils down to a few key questions you need to ask:
What is the task or problem you are trying to solve?
Where and how will you use the output?
Which tool are you most comfortable using?
Before we dig further into these questions, let’s start with comparing Mapping and Wrangling Data Flows.
