Session resources: Power BI dataflows and Azure Data Lake integration

Last week I delivered two online sessions on the topic of integrating Power BI dataflows with an organizational Azure Data Lake Storage Gen2 storage account. I’ve blogged on this topic before (link | link | link | link) but sometimes a presentation and demo is worth a thousand words.

On April 30th I delivered a “Power BI dataflows 201 – beyond the basics” session for the PASS Business Intelligence Virtual Chapter. The session recording is online here, and you can download the slides here.

On May 4th I delivered a “Integrating Power BI and Azure Data Lake with dataflows and CDM Folders” session for the SQL Saturday community event in Stockholm, Sweden. I was originally planning to deliver the Stockholm session in person, but due to circumstances beyond my control[1] I ended up presenting remotely, which meant that I could more easily record the session. The session recording is online here, and you can download the slides here.

Each of these sessions covers much of the same material. The Stockholm presentation got off to a bit rocky start[2] but it gets smoother after the first few minutes.

Please feel free to use these slides for your own presentations if they’re useful. And please let me know if you have any questions!

[1] I forgot to book flights. Seriously, I thought I had booked flights in February when I committed to speaking, and by the time I realized that I had not booked them, they were way out of my budget. This was not my finest hour.

[2] The presentation was scheduled to start at 6:00 AM, so I got up at 4:00 and came into the office to review and prepare. Instead I spent the 90 minutes before the session start time fighting with PC issues and got everything working less than a minute before 6:00. I can’t remember ever coming in quite this hot…

Upcoming Dataflows Presentations

I’m not dead!

After having a prolific first few months with this blog, the year-end holidays disrupted my routine, and I’ve been struggling to get everything balanced again. 2019 has been great so far, but its also been stupid crazy busy, and while blogging has been on my backlog, it just hasn’t made the bar for implementation.

Until now, I guess…

Last week I was in Darmstadt, Germany for the SQL Server Konferenz 2019 event, where I presented on Power BI dataflows. My session was well-attended and well-received[1] but I realized that I’d never actually told anyone about it. Now it’s time to correct this oversight for some upcoming events. These are the public events where I’ll be speaking over the next few months:

Event: SQL Saturday #826

Location: Victoria, BC, Canada

Date: March 16, 2019

Session: Introduction to Power BI dataflows

Event: Intelligent Cloud Conference

Location: Copenhagen, Denmark

Date: April 9, 2019

Session: Integrating Power BI and Azure Data Lake with dataflows and CDM Folders

Pro tip: If you’re attending Intelligent Cloud, be sure to attend Wolfgang Strasser‘s “Let your data flow” session earlier in the day. This session will provide a great introduction to Power BI dataflows and will provide the prerequisite knowledge necessary to get the most out of my session.

Event: SQL Saturday #851

Location: Stockholm, Sweden

Date: May 4, 2019

Session: Hopefully two dataflows sessions[2], details still being ironed out.


[1] Except for that one guy who rated the session a 2. I’d love to know what I could have done to improve the presentation and demos

[2] Also, swords.

Dataflows, or Data Flows?

I don’t hear this question as often as I used to[1], but I still hear it: What’s the difference between dataflows in Power BI and Data Flows in Azure Data Factory?

I’ve already written extensively on the Power BI side of things, and now the awesome Merrill Aldrich from BlueGranite has published an excellent overview of the ADF feature on the BlueGranite blog. You should check it out here:

I’m not going to summarize the similarities and differences in this post, but after you’ve read Merrill’s article, I’d love to hear your specific questions.

[1] This may or may not be because I’ve been on vacation for the past three weeks.