At SQLBits 2019, I co-presented the Azure Data Factory Deep Dive with Jason Horner (@jasonhorner). We received great and actionable feedback from our attendees (thank you!) and have been working on improving the session since then. That includes everything from moving sections around for a better flow, to adding newly released features like Wrangling Data Flows.
Since I will be presenting these deep dives alone, I have also made some additional changes. Without an experienced trainer like Jason by my side, I’m not entirely confident running hands-on labs during the day. Instead, I will be focusing on delivering the best and most updated content I can, and let attendees work through labs on their own :)
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.
PASS turns 20 this April! To celebrate 20 years of educating data professionals, they are organizing a 24 Hours of PASS with the theme Past Learnings and Future Visions. From April 3-4, you can watch 24 free webinars back-to-back. If you can’t attend all 24 webinars live (who can!?), they will all be recorded. Woohoo!
In January 2019, I was honored to be asked to contribute to the PASS Insights BI Edition Newsletter. I said yes, of course! :) I chose to create an Azure Data Factory Data Flows introduction video. This is a sneak preview of the upcoming Data Flows feature, with a quick walkthrough of how easy it can be to create scalable data transformations in the cloud – without writing any code!
Please note: As of January 2019, when I recorded this video and published this blog post, Azure Data Factory Data Flows is still in preview. Features will be added and things will get changed, just like all the other Azure products. But! Hopefully this shows what you can look forward to.
At the end of this blog post, I have tried to answer some frequently asked questions about Azure Data Factory Data Flows.