This is a quick post to highlight my recent appearance on the Data Radicals podcast (Apple, Spotify), hosted by Alation founder and CEO, Satyen Sangani. I’ve worked with Alation for a long time in varied capacities — e.g., as an angel investor, advisor, director, interim executive, skit writer, and probably a few other ways I can’t remember. This is a company I know well. They’re in a space I’m passionate about — and one that I might argue is a logical second generation of the semantic-layer-based BI market where I spent nearly ten years as CMO of Business Objects.
Satyen is a founder for whom I have a ton of respect, not only because of what he’s created, but because of the emphasis on culture and values reflected in how did it. Satyen also appreciates a good intellectual sparring match when making big decisions — something many founders pretend to enjoy, few actually do, and fewer still seek out.
This is an episode like no other I’ve done because of that history and because of the selection of topics that Satyen chose to cover as a result. This is not your standard Kellblog “do CAC on a cash basis,” “use pipeline expected value as a triangulation forecast,” or “align marketing with sales” podcast episode. Make no mistake, I love those too — but this is just noteably different content from most of my other appearances.
Here, we talk about:
- The history and evolution of the database and tools market
- The modern data stack
- Intelligent operational applications vs. analytic applications
- Why I feel that data can often end up an abstraction contest (and what to do about that)
- Why I think in confusing makets that the best mapmaker wins
- Who benefits from confusion in markets — and who doesn’t
- Frameworks, simplification, and reductionism
- Strategy and distilling the essence of a problem
- Layering marketing messaging using ternary trees
- The people who most influenced my thinking and career
- The evolution of the data intelligence category and its roots in data governance and data catalogs
- How tech markets are like boxing matches — you win a round and your prize is to earn the chance to fight in the next one
- Data culture as an ultimate benefit and data intelligence as a software category
I hope you can listen to the episode, also available on Apple podcasts and Spotify. Thanks to Satyen for having me and I wish Alation continuing fair winds and following seas.
Hi Dave,
Am a big fan of your very inspiring newsletter! Many thanks for it!!
At around minute 10, you talk about whether the model should be in a Git repo or Alation. We advocate what we call Metadata-as-Code whereby the data model (which I grant you is a totally different thing than an AI model) should reside in Git and get sync’d with the data catalog (Alation or other). See more details at https://hackolade.com/metadata-as-code.html
Let me know your thoughts
Looks interesting, thanks for sharing. As you know, I was headed the other directions: are (AI/ML) models code or data because it’s data training code — and do they rightfully belond in a code repository or data catalog. You’re basically asking: is metadata code or data. My first order argument is data is data, so data about data (metadata) is ergo data, not code. I think you’re saying, kinda regardless, that it should be managed like code and it’s not something I’ve thought about before. Hard to disagree with sync’ing it. I need to percolate more on the idea. See the other comments about “abstraction contests” earlier in the cast :-)