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Watch the on-demand discussions of the latest trends in data and AI
EVP of the Oakland As and Creator of Moneyball
A Fireside Chat with Billy Beane, Baseball’s First Data-Driven General Manager
Few pop culture icons bridge the divide between sports and data analytics like Billy Beane, EVP of Baseball Operations and minority owner of Major League Baseball’s Oakland Athletics (As) and the pioneer between moneyball, the practice of applying statistical analysis to scouting and analyzing players. Billy and his data-driven approach to baseball led the As to several division champions and the unique distinction of being the only team in 100+ games of American League Baseball to win 20 consecutive games. Billy’s accomplishments were the inspiration behind Michael Lewis’ award-winning book, Moneyball: The Art of Winning an Unfair Game, and the subsequent major motion picture with Brad Pitt.
Lessons in Poker, Data Science, and Life with Annie Duke
Have you ever had to make a decision when you don’t have all the facts? If you’re nodding your head, welcome to the club! The good news? There are some tips and tricks you can apply to make good decisions with less data – or think in bets. Annie Duke, former professional poker player and professional decision strategist, will join Monte Carlo CEO and co-founder on the IMPACT stage for a wide-ranging conversation about how data practitioners and leaders can work with limited data to make smarter decisions.
Author. Professional Speaker. Decision Strategist.
VP of Product,
Google DeepMind
A Fireside Chat with Google DeepMind’s SVP of Product, Eli Collins, on Building Responsible AI
Eli Collins is the VP of Product for Google DeepMind, where he’s responsible for setting strategy for DeepMind’s product teams, including the organizations building Bard, Imagen, and other AI tools. Previously, he was the Technologist-in-Residence at Accel and the Chief Technologist, VP of Engineering, at Cloudera.
Hear from today’s preeminent data leaders and architects about what it takes to drive impact with your data and AI at scale. Learn about the latest technologies, strategies, and processes paving the path forward for our industry and discover what it takes to achieve reliability for your data. From data platforms and data governance to data contracts and generative AI, IMPACT will shed light on how today’s top technical teams are designing performant and impactful data and AI products your business can trust.
SVP of Product Management,
Salesforce
Field CTO, Snowflake
VP of Analytics & Strategy,
Fox
VP of Data & Integration,
Navan (TripActions)
VP of Analytics,
BetterUp
VP of Engineering,
Credit Karma
VP of Analytics and Digital Transformation,
Collaborative Imaging
Software Engineer,
Whatnot
Co-Founder & CEO,
dbt Labs
Co-Founder,
Atlan
Co-Founder & CEO,
Fivetran
General Partner,
Theory Ventures
Director of Data,
Pie Insurance
Staff Data Analyst,
Sojern
Senior Principal Data Product Manager, OVO
Senior Data Engineer,
Tools for Humanity
Data Scientist,
OVO
Analytics Engineer,
Tools for Humanity
Analytics Engineering Manager,
Hubspot
Director, Data & Technology,
Dr. Squatch
VP of Product
Google DeepMind
Senior Engineering Manager,
Wayfair
CEO,
Workstream
CEO & Co-Founder,
Monte Carlo
Co-Founder & CTO,
Monte Carlo
Sales Engineer,
Monte Carlo
Co-Founder and President,
Omni
Senior Director of Product for AI/ML,
Databricks
VP of Strategy and Alliances,
Cube
Announcing new speakers every week!
Check out the on-demand sessions that’s available to watch!
Main Stage
Main Stage
Main Stage
Main Stage
Accelerating the Impact of Data
Designing Trusted Data Products
Building Reliable Data & AI Stacks
Accelerating the Impact of Data
Designing Trusted Data Products
Improving data quality is a top priority for Data Engineering teams. Identifying critical data issues and notifying the specific business stakeholders to fix are both critical steps in the data observability journey. Often data engineering teams are caught in the middle. This can drain data engineering resources and lead to delays in getting the data corrected.
Ed Presz, Director of Data at small business insurance leader Pie Insurance, shares how his team built an incident detection and notification workflow with Monte Carlo and Slack to drive domain-oriented ownership of data quality for business stakeholders across their company. He'll discuss the process, culture, and technologies necessary to introduce self-serve incident resolution and share the positive impact this shift has had on his team and the business at large.
Building Reliable Data & AI Stacks
Accelerating the Impact of Data
Designing Trusted Data Products
Building Reliable Data & AI Stacks
Data without trust is worthless—because the people inside your organization won’t use data if they don’t trust it. And worse, if they’re using bad data, they could come to the wrong conclusion when making a critical decision.
For more than a decade, data teams have been constantly answering the same repetitive and annoying questions from business users. The worst of these are arguably “Does this data look right?” or “When was the data updated?” or “How do I use this?”
In this session, you’ll learn how to establish a culture of data knowledge powered by new investments in Monte Carlo, so your data teams can automate all of those annoying questions away. From streamlining communications with your business teams around incident detection and resolution to exposing data status pages for everyone, learn how to ensure your people can confidently leverage data to impact outcomes – without all the hand-holding.
Building Reliable Data & AI Stacks
Trust between data teams and business users is hard won and easily lost. Modern data observability tools play a well-established role in maintaining that trust by focusing on data, AI, and pipeline reliability. Learn how Semantic Layers help maintain this data trust by maintaining consistent metric definitions, business logic and security policies between data sources and downstream applications.
Building Reliable Data & AI Stacks
Accelerating the Impact of Data
Designing Trusted Data Products
Building Reliable Data & AI Stacks
Gen AI isn't the solution, it’s the UI. LLMs are powered by the context of the world, but running AI on your own data needs much greater specificity. And with that comes great data quality responsibility - requiring a good data model and human refinement.
The rise of Gen AI lowers the barrier to accessing data, bringing a greater risk for bad data, decisions, and outcomes. While nearly every data tool has some AI, the devil is in the details. Hallucination, non-deterministic results, and nuanced analysis require human-in-the-loop user experience. There’s too much hype and not enough how. Join this session for tips and tactics to help you guard against bad data robots and drive real value with AI.
Accelerating the Impact of Data
Building Reliable Data & AI Stacks
Designing Trusted Data Products
What’s next for the future of data? Will GenAI bots eat me? When will my stakeholders stop pinging me? Who knows! But one thing’s for sure: Monte Carlo’s Reliability Pioneers have some thoughts! Join us for a wide-ranging panel discussion with data leaders from HubSpot, Collaborative Imaging, and Dr. Squatch about their predictions for the future state of data and AI and what this means for the future of our work.
Topics to be discussed: building reliable data stacks that can support GenAI use cases, consolidated vs. best-of-breed stacks, operationalizing data observability, and much more!
Main Stage
Main Stage
Building Reliable Data & AI Stacks
We’re also coming to a city near you!
Get ready for the big day by joining your regional peers for an IRL (in real life) IMPACT Meetups. The Meetups will feature lightning talks, panel sessions, and networking with your peers on what it takes to drive IMPACT with your data. Topics include building reliable data platforms, scaling data product development, setting strategy for data governance, getting started with data observability, and more.
You don’t want to miss it!
See IMPACT 2022 on demand
Have a story to tell? Submit for an opportunity to present your learnings about scaling more reliable data and AI systems at IMPACT: The Data Observability Summit.
IMPACT is Monte Carlo’s annual summit for data leaders and architects dedicated to sharing thought leadership, best practices, and advice about what it takes to drive impact with reliable data and AI at scale! Now in it’s third year, IMPACT brings together the data community to showcase the latest and greatest trends, technologies, and processes in data quality, large-language models, data and AI governance, and of course, data observability.
IMPACT welcomes data, ML, and AI leaders and architects charting the path forward for their company’s data reliability initiatives, from implementing data governance programs to building trusted data stacks and training LLMs powered by high quality data. Whether you’re just looking to learn more or want to dive deeper into best-in-class data and ML management strategies, IMPACT is the event for you.
IMPACT will be held virtually in the Airmeet event platform. After registering you will receive an email with a unique link to join the event. We welcome you to check out the event before it starts to bookmark your favorite sessions and set up your profile. You can find a full guide on using the event platform here!
Yes! Sessions will be recorded and available on demand post event. A majority of our sessions are live however, so make sure to join day of to get the full experience!
Send us a message at [email protected].
Join some of today’s top data leaders and architects at IMPACT: The Data Observability Summit as they share best practices for scaling data reliability as technologies, processes, and culture. Learn how to make a real IMPACT with your data.