Billy Beane, Generative AI, and Data Observability: 5 Reasons Why I’m Excited About IMPACT 2023 – And You Should Be, Too

I’m not sure what’s harder to believe – that we’re just a week away from IMPACT OR that it’s our third iteration of the world’s only Data Observability Summit! 

2023 has been a crazy year in data, with the rise of GenAI and LLMs eclipsing nearly everything else in tech. tk4,There’s plenty of hype – don’t get me wrong – but there’s also a lot to be excited about, and our speakers will address these opportunities, challenges, and forward-looking predictions for data and AI teams. They’ll also touch on how to get your data reliability foundations right for AI, data product development, operational analytics, and other business critical initiatives. 

During this year’s IMPACT, we have more surprises up our sleeves than ever before, from exclusive AMAs with keynote speakers to interactive sessions highlighting how the best teams scale data quality for their AI applications and more. 

Hear from data & analytics icons who were ahead of their time

When we pooled our community about the data leaders they’d most like to hear from at this year’s IMPACT, two names rose to the top of the list: Billy Beane and Annie Duke. For those unfamiliar, Beane is the pioneering former general manager of the Oakland As who brought data & analytics to baseball, fielding a team of rookie players based on runs and getting to base vs. building a team around more expensive all-stars. 

Duke is the similarly pioneering World Series of Poker champion and statistics PhD whose turned her experiences at the poker table into a series of best-selling books about decision strategy, including Quit: The Power of Knowing When to Walk Away and Thinking in Bets: How to Make Smarter Decisions, and currently serves as Special Partner in Decision Science at First Round Capital. 

Keep tabs on what’s new and novel in the world of AI and LLMs

AI is front and center this year at IMPACT, with a focus on how to identify impactful generative AI use cases and best practices for training your large-language models (LLMs). 

We’ll have talks from Nga Phan, SVP of Product Management at Salesforce AI, Tomasz Tunguz, General Partner at Theory Ventures, and Neta Iser, VP of Data and Integration at Navan (formerly TripActions) for fireside chats and presentations on how today’s data and AI leaders are going beyond the hype to operationalize enterprise-ready generative AI. 

In this vein, our third and final keynote will feature Eli Collins, VP of Product at Google DeepMind, in a wide-ranging discussion with our CEO and co-founder Barr Moses about all things AI – from the origins of our current “AI revolution” to whether RAG or fine-tuning makes LLMs more accurate and reliable. 

Another AI-focused session not to miss? Pioneering the Modern Data & AI Stack with Tristan Handy, CEO and co-founder of dbt Labs, George Fraser, CEO and co-founder of Fivetran, and Prukalpa Sankar, co-founder of Atlan, about what’s next in MDS tech, particularly as it relates to readying our pipelines for AI applications. 

And be sure to stay tuned for our end of day product session with Monte Carlo CTO and co-founder, Lior Gavish, for a sneak peek into what we have planned to make reliable, enterprise AI a reality for companies everywhere. 

Build the foundations of your modern data and AI strategy

Generative AI, LLMs, and RAG may be the talk of the town LinkedIn, but sometimes it’s important to take a step back and make sure we have our bases covered, whether that’s taking the time to invest in building a strong and supportive team culture to choosing the right technologies for your stack. 

Several of our sessions will highlight how today’s top data and AI leaders are setting the groundwork for success with the right tooling, processes, and organizational structures so that when GenAI (and any other initiative your CEO wants you to prioritize) comes knocking, you’ll be ready to go. 

Personally, I couldn’t be more excited for Cameran Hetrick’s, VP of Analytics at BetterUp, session about how to become a purpose-driven data leader, taking cues from her company’s own product, the BetterUp coaching platform, to build and lead a balanced and fulfilled data organization. 

Learn how the experts scale best-in-class data observability

Historically, IMPACT has focused on highlighting the most cutting edge trends, technologies, and thought leadership in the data and AI space. And don’t get me wrong, that’s still very much what this event is about. 

Due to popular demand from the broader community, we’re hosting a few sessions focused exclusively on spinning up and scaling repeatable data observability workflows, featuring our very own customers. Who better to learn from than the pioneers of data observability themselves? 

Can’t wait for our session with Jessica Cook, Staff Data Analyst at Sojern, Georvic Tur, Senior Data Engineer at Tools for Humanity, and Daniel Mas Buitrago, Sr. Analytics Engineer at Tools for Humanity on the 12 ways data teams can optimize their data observability ROI today.

Come for the sessions, stay for the skits, music, and giveaways!

No virtual conference would be complete without a video game / late ‘80s inspired DJ set courtesy of Orchkeystra, songs poking fun at the crazy world of data, and exclusive giveaways for our most engaged attendees. 

Last year, we got in the Halloween spirit with “Emails Mad at Me,” a song dedicated to the lone data engineer in our lives, and in 2021, we hopped on the country train with “Achey Breaky Chart.” What will we release this year? You’ll have to tune in to find out! 

We’ll also be giving away 50 copies of keynote speaker Annie Duke’s latest book, Quit: The Power of Knowing When to Walk Away, to the most spirited and engaged participants in our sessions and networking rooms. 

And this just scratches the surface.

So, what are you waiting for? RSVP already!

PS – special shout out to our sponsors: Snowflake, Workstream, Omni, Databricks, data.world, cube, and Gable for helping us throw an awesome summit. See you there.

PSS – if your favorite video game of the late 80s isn’t Tetris, are you really a data engineer?