Recap: New York City Data Universe 2024

New York City hosted another great data, analytics, and AI conference: Data Universe 2024. This is the first year for this conference in the United States; they have had very successful events in London in the past few years.

The conference featured a novel format with seven open stages around the exhibit hall. Stages were specific to topics:

• Keynotes
• Analytics & Business Intelligence
• Business Strategy & Transformation
• Data Engineering & Infrastructure
• Emerging Technology, Society, & Ethics
• Governance, Privacy, & Security
• Modern Architecture, Data Products, & AI

Attendees were given headphones tuned to the speaker on stage. The format allowed for an overflow audience when necessary. It also allowed for peeking at the slides of your second choice session to get a taste of both topics.

The app made it easy to know where you were going and what topics were available at any given time. It also had a map to make sure you could find the right stage.

The Keynote stage provided the opportunity to listen to several great speakers in row.

Alistair Croll—board member and well-known author—gave the opening keynote on Building the Second Stack. He highlighted that we are in a Great Acceleration. He discussed the transition from traditional software, where we tell it what to do to generative AI, which is software that tells us what to do. He predicted that “Everything qualitative will become quantitative.”

Jana Eggers—CEO of Nara Logics—spoke about the journey of AI from behind the scenes to mainstream. She discussed AI literacy. She cautioned that reducing things to the MEAN may not capture human creativity. We use explainability with abstraction. She highlighted the shift from a model to a system of AI tools. Using Job Crafting as an example she described how recruiters are benefiting from AI today. It’s important to know how to use the tools, but also when to be skeptical. As we are all in the early stages of AI we need to remember, “It’s not just about the tools, it’s the culture.”

Doug Laney—well-known author of Infonomics and Director at West Monroe Partners—gave another great presentation on valuing data. In Volume, Velocity, and Variety he started by encouraging us to give up the metaphor of “Data is the new Oil.” Even though in both it is hard to clean up after a spill. The main difference is that Data is not a depleting asset—when we use data, we create more data.

David Boyle—co-author of the PROMPT book series—presented on the impact Language Models have on our careers. It is easy for organizations to misunderstand Language Models. Data is about numbers and language is about ideas. The whole point of numbers is to get to ideas. Now we have a tool to make it easier. We can do analytics on ideas just as we have used analytics on data.

There was plenty of networking time. And with the exhibitors right there, we had more time to talk about their offerings. Of course, there was some great swag! My new Data Rebel T-Shirt from Starburst officially tops the list of best swag ever! The DataVengers were there in force making every moment fun! I got to introduce the IT BEE (Scott Taylor’s puppet) that only speaks in Buzzzz Words to my new puppet, Morgan Templater who makes governance easier with templates. (If you don’t know what I’m talking about, go to this link on YouTube).

Women in Analytics hosted a great panel of women and a lovely breakfast.

Justin Borgman and Subodh Kuman reminded us that there is still distance between AI aspirations and Data Foundations. This was a fairly common theme: “AI has Taken Off, but Where is it Going?”, “Winning in an AI World: How and Where AI fits in your data strategy,” “The Rise of Modern Data Management.” “Is your Data Ready for AI?” and all that just on the first day!

Day 1 ended for me with “The Great Data Debate.” Mike Ferguson hosted Cindi Howson, Drew Banin, Shaun Clowes, and Tirthankar Lahiri in a lively debate spanning the use and dangers of GenAI, industry trends, modern data architecture and AI Governance.

Day 2 was full of talks by the DataVengers, George Firican, and Sadie St. Lawrence. We ended the day with some fun Swag giveaways.

Peggy Tsai gave great advice on the five things CDOs should know to build an AI-first organization:

1. AI Strategy is Data Strategy: AI is only as good as the data underlying it and used to train
   it.
2. Leverage Data Capabilities for AI: The Data Governance Council > AI Governance Council, Data Catalog > AI model and data inventory, Data Classification > Labels for model access
   and usage, Data Quality/Metrics > Potential data bias and toxicity, Data Lineage > Traceability of AI model to underlying data, and Retention Policies> Stale data from training sets.
3. Privacy laws are changing both Federal and state laws are under consideration
4. Build in Security for AI: Ensure training data has no PII
5. AI Literacy and Culture: Expand your Data Literacy training to AI Literacy and Culture. Standardize AI terminology and nomenclature with everyone.

Overall, it was full of great content, but was also a lot of fun. I’ll be going back next year!