On Data Engineering in 2018

A few years ago I had a conversation with Scott Currie, the CEO of Varigence and inventor of Biml. Scott is one of the smartest people I know and I know a lot of very smart people. Whenever I have the opportunity to communicate with the very smart people I know, I often ask them – based upon their knowledge of me and what I do and any plans I have shared – for advice on stuff I should focus upon moving forward. Scott’s monosyllabic reply to this question?


Over the course of the past couple years I’ve shared – on this blog, even – some of my experiences learning more about Apache Spark. While I expected a little resistance, I was a little surprised by the… intensity… of some of the private messages and emails I received. As I replied to the intense people (and there were only a few), I could stop learning stuff right now, today, and continue working with SSIS for the next decade or so. I believe the same goes for anyone working with SSIS today.

I’m not going to stop learning stuff.


I love SSIS. But I don’t use SSIS because I love it. I love SSIS because it solves a particularly difficult piece of the story of enterprise data: data integration and data engineering. I feel a similar way about writing (and I’ve blogged recently about writing). I write because I like to write, not for clicks or branding or any of the other benefits I glean from writing. I consider those benefits cool, but side-effects of my desire to write.

The same goes for SSIS: I love SSIS because it solves a problem that I want to solve. I hope that makes sense.

Why Spark?

Two reasons:

  1. Spark is taking a more prominent role in SQL Server 2019.
  2. Spark is the engine beneath Azure Data Factory Data Flows.

How can you learn more about Spark? There are bunches of videos out there on YouTube. YouTube is crowd-sourced and free, which makes it awesome. The quality of YouTube training is crowd-sourced and free, which is a challenge.

I learned a lot from edX. I’m a fan of how edX approaches MOOC (online education). They offer lots of courses for free, which means you can grow your knowledge by investing only time. It’s tough to beat $free. If you want, you can pay for a certificate which you can then add to your online resume or LinkedIn profile like I added this one.


My advice? Spend some time learning. Pick your favorite learning platform and jump in. If you have SQL Server and / or SSIS experience, you already know a lot about the problem enterprises are trying to solve with data engineering tools. That’s a good place to be, but not required.

Keep learning!


Andy Leonard


Christian, husband, dad, grandpa, Data Philosopher, Data Engineer, Azure Data Factory, SSIS, and Biml guy. I was cloud before cloud was cool. :{>


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