Marketing is a well-established field, yet there is still a massive gulf between CEO and CMO expectations. If CMOs are still trying to get traction with their CEOs, what hope do Chief Data Officers have? I rant about this.

WSJ article: Divide Between CMOs and CEOs is Growing: https://www.wsj.com/articles/divide-between-cmos-and-ceos-is-growing-research-finds-a73374f4?st=bcayeo7wc9j18fd&reflink=desktopwebshare_permalink

Bill Inmon and I sat down in his home over a weekend to tell me the history of the data industry. This is a very rare and wide-ranging conversation about the dawn and evolution of the data industry, straight from the godfather himself.

In my global travels, I've spoken to countless practitioners and leaders in the data field. I discuss two common themes of questions I get - "How do I work with the business?" and "What tools should I use?"

Matt Sharp and Chris Brousseau join me to chat about writing their new book "LLMs in Production" (Manning). What's it like to write a book in a field that's changing at light speed? How do two people write a book together? We dive into this and much more.

Note - we recorded this outside at the Utah State Capitol. There's a bit of background noise, but it hopefully doesn't distract from the conversation. It was too nice of a day to be stuck inside :)

I’m at the Gitex Dubai conference. It’s huge, with 170k in attendance! There’s a lot of hype about AI. I unpack my thoughts on the latest AI hype cycle in my usual ranty manner. Enjoy!

Johnny Graettinger (CTO of Estuary) joins the show to give a clinic on streaming and immutable logs. We cover a lot of ground in this technical deep dive. Enjoy!

Estuary: https://estuary.dev/

Gazette: https://gazette.readthedocs.io/en/latest/

Github (Estuary Flow): https://github.com/estuary/flow

LinkedIn: https://www.linkedin.com/in/johngraettinger/

Just wrapped up DEWCon, a great data engineering conference in Bangalore, India. I've participated in most data engineering events around the world this year, and I keep seeing the same things - data engineers seek guidance, mentorship, and a sense of best practices. I think we can build a global data engineering community that helps data engineers level up and share their experiences.

Bob Muglia joins the show to talk about why we need to move beyond SQL, semantic models, the power of knowledge graphs, the past, present, and future of databases, and much more.

Bob has a storied history in the data space, having significant involvement with Microsoft Office, SQL Server, Snowflake (former CEO), and much more. It's rare to meet someone with such a deep involvement in the creation of our industry, and this was a fascinating conversation.

Also, check out Bob's book, "The Datapreneurs." One of the best books about the data industry I've read in ages.

LinkedIn: https://www.linkedin.com/in/bob-muglia/

X: https://twitter.com/Bob_Muglia

Book: https://www.amazon.com/Datapreneurs-Promise-Creators-Building-Future-ebook/dp/B0BZQFJ5RP

As I've ranted for a while now, I think our biggest challenge as an industry is the knowledge and skills to do our properly do our jobs. Too often, I see data professionals flounder on seemingly simple problems, even using the hottest, coolest technologies. Don't blame the tool, blame the user.

How do you sharpen your skills? I give some advice in this episode.

Egor Gryaznov joins me to chat about the "Non-Modern Data Stack", getting out of our data bubble, and much more. If you like a refreshing conversation talking about the past, present, and future of our industry, this is for you.

BigEye: https://webflow.bigeye.com/

LinkedIn: https://www.linkedin.com/in/egorgryaznov/

Vendors are an integral part of conferences (they pay for them, for one). But what happens when vendors face a tough market? Between higher interest rates, a tough funding environment, and a lukewarm market for what vendors are selling, what happens? I unpack some thoughts on what I think 2024 will look like for vendors at conferences.

Jason Taylor and I chat about low-key data happy hours, getting outside of your comfort zone, finding new ideas, the divides in the data space, fighting dumpster fires, and much more. This is a wide-ranging chat about a lot of key topics in the data space. Enjoy!

LinkedIn: https://www.linkedin.com/in/jasonbennetttaylor/

Michel Tricot (CEO of Airbyte) joins me to chat about the impact of AI on the modern data stack, ETL for AI, the challenges of moving from open source to a paid product, and much more.

Airbyte & Pinecone - https://airbyte.com/tutorials/chat-with-your-data-using-openai-pinecone-airbyte-and-langchain

Note from Joe - I had audio issues cuz he got a new computer and didn't use the correct mic :(

Juan Sequeda and I chat about knowledge graphs (he's an OG in this area), the potential of LLMs on structured datasets, and much more. This is an honest, no-BS chat about the transition from a data-first world to a knowledge-first world. Enjoy!

LinkedIn: https://www.linkedin.com/in/juansequeda/

data.world: https://data.world/product/

website: https://www.juansequeda.com/

Nowadays, it seems like lots of people want to become data influencers and content creators. Ravit Jain and I chat about how to build an audience, the power of LinkedIn, and much more.

The Ravit Show: https://theravitshow.com/

LinkedIn: https://www.linkedin.com/in/ravitjain/

Boring is back. As technology makes the lives of data engineers easier with respect to solving classical data problems, data engineers can now move to tackle "boring" problems like data contracts, semantics, and higher-level and value-add tasks. This also sets us up to tackle the next generation of data problems, namely integrating ML and AI into every business workflow. Boring is good.

Medical data is a mess. Aaron Neiderhiser and Coco Zuloaga from Tuva Health are here (at my house) to answer why this data is insanely complex, and what can be done to fix it. They take a first-principles approach that you might find interesting.

In my travels and virtual conversations with data teams and practitioners around the world, the same thing keep popping up - data teams feel misunderstood and under-appreciated. If we're going to make progress as an industry, it's time to stop playing defense, and start playing offense.

David Foster just published the 2nd edition of his amazing book, Generative Deep Learning (O'Reilly 2023). We chat about a lot - running a consultancy, all things writing, the impact of AI on kids, why in-person events matter more than ever, and much more.

David's LinkedIn: https://www.linkedin.com/in/davidtfoster/

Book (Amazon): https://www.amazon.com/Generative-Deep-Learning-Teaching-Machines/dp/1492041947

Applied Data Science Partners: https://adsp.ai/

The massive attention on AI means the data industry has a shot at finally succeeding with the things we've been struggling with for decades - "adding value", data quality and modeling, governance, etc. For AI to work, these things need to properly function. But are we up for the task? And if we can't get it right NOW, when?

Whenever Kevin and I get together, we "nerd snipe" each other. This conversation is no different, and it's a wide-ranging conversation about how the data landscape evolves alongside LLMs, education, startup mentorship, and the possible (looming?) startup mass extinction.

Kevin's LinkedIn: https://www.linkedin.com/in/kevinzenghu/

Metaplane: https://metaplane.dev/

Matt Housley hangs out at my house and we chat about Data NIMBYism and gatekeeping. What is that? Listen and find out.

Gordon Wong has led data teams of all sizes, across many well-known companies. I consider him a Yoda in the data field, and this is a glimpse into the monthly chats that Gordon and I have. Unfiltered and uncut. Enjoy.

Please note - we had to cut it a bit short, as Gordon had another call at the top of the call. Again, this is literally a look at a normal chat that Gordon and I engage in.

This week I had the opportunity to give two talks to two very different groups. Earlier in the week I spoke with a group of senior and above software engineers and leaders in Utah. Yesterday I spoke with a group of data engineers and leaders in Atlanta.

The common theme? There's a big divide between dev and data, and data's often on the losing side of this divide. For data teams to be more successful, we need to close the divide and collaborate more closely with dev, and vice versa.

Vin and I chat about the challenges of writing books, how companies can mature with data science, why data scientists need to learn strategy, and much more.

(We experienced a slight internet delay around the 15:30 mark, otherwise great)

LinkedIn: https://www.linkedin.com/in/vineetvashishta/

Book: https://www.amazon.com/Data-Profit-Businesses-Leverage-Bottom/dp/1394196210

Site: https://www.datascience.vin/

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