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.
Last year at Microsoft Ignite, I was fortunate enough to interview Mike Flasko and Sanjay Krishnamurthi. This year, I got to have a follow-up chat with Mike Flasko and Sharon Lo! We talked about the recent and upcoming Azure Data Factory updates :)
In this interview, Mike and Sharon share the highlights from their session at Microsoft Ignite 2018. What are visual Data Flows? How are Azure Data Factory Data Flows different from the recently announced Power BI Dataflows? What’s on the Azure Data Factory roadmap? And finally, how can you provide feedback and get involved in private previews?
Azure Data Factory Updates with Mike Flasko and Sharon Lo
(I apologize for the unsteady video :( Unfortunately, I didn’t see how shaky it was until post-production. If it gets too distracting to watch, please just listen. Mike and Sharon share a lot of interesting things :) )
Thank you so much to Mike and Sharon for chatting with me on a busy day!