Opening Keynote | Main Stage

Architecting the Future of Reliable Data + AI in the Enterprise

As the pioneers of the data observability category, we’re excited to show you how we’re helping organizations rise to the next stage of their data quality journey.

Join Monte Carlo co-founder and CTO, Lior Gavish, for a deep dive look into our product roadmap, including new integrations, GenAI capabilities, and more to operationalize data quality detection, triage, and resolution at scale for trusted data and AI. 

Keynote Speaker | Main Stage

The 13 Keys to Reliable Predictions: A Fireside Chat with Presidential Predictor Dr. Allan Lichtman

As data and AI leaders, we’re tasked with helping businesses and other organizations make better data-driven decisions. The same statistical models and modes of prediction can also be applied to elections - just ask Dr. Allan Lichtman. Lichthman is an award-winning historian and creator of the Keys to the White House Model, which uses 13 true/false criteria to predict whether the presidential candidate of the incumbent party will win or lose the election. 

During this fireside chat, Dr. Lichtman will share how he developed his 13 Keys, the role of history vs. circumstance when it comes to data analysis, and how he’d revise his presidential prediction models almost 50 years later. We’ll also dive into the role of AI in electoral predictions and what this evolving technology means for the future of democracy. 

Data Leaders Breakout Track | Leading with Data + AI

Trust and Privacy by Design: Drata’s Ethical Use of Data in AI

In the rapidly evolving world of compliance automation, safeguarding client data isn’t just a priority — it’s the cornerstone of trust, integrity, and it’s something that Lior Solomon, VP of Data Engineering at Drata, takes seriously. 

In this session, Lior will explore how Drata’s responsible AI practices, combined with advanced data observability, set new standards for privacy, trust, and reliability in the industry. Discover how Drata integrates privacy by design, enforces strict data governance, and utilizes data observability to build AI systems that not only advance technology but also earn and maintain customer trust.

Data Practitioners Breakout Track | Pioneering Data Observability

Crafting Effective Data Quality Reports: Building Trust and Democratizing Data at Payoneer

Payoneer, a global leader in cross-border payments, is at the forefront of transforming how data teams instill trust in data through a relentless focus on data quality and democratization. From defining clear goals and calculating data trust scores to implementing targeted strategies that improve satisfaction across user groups, Payoneer is setting a new benchmark for data-driven success in the financial sector.

Join Eli Genislaw, Senior Director of Data Engineering at Payoneer, to hear his approach to reporting on the state of data quality and democratization, and best practices for how you can implement these strategies at your organization.

Data Leaders Breakout Track | Leading with Data + AI

5 Unexpected Ways Data and AI Will Evolve in 2025

“The data and AI space moves fast. If you don’t stop and look around once in a while, you just might miss it,” said Ferris Bueller if he was in tech, probably. No one knows this more than Tomasz Tunguz, General Partner at Theory Ventures and investor in Looker, Motherduck, Monte Carlo, Hex, and other pioneering data companies. In this talk, Tomasz will walk through the top 10 trends he sees defining data and AI in 2025, including the rise of ML engineers, the evolution of the LLM production stack (vector databases, anyone?), the role of data observability in generative AI deployment, and the explosion of query engines, among other critical technologies.

Data Leaders Breakout Track | Leading with Data + AI

Transforming Data into Value: Implementing Development Best Practices for High-ROI Data Products

In today's data-driven business landscape, developing data products that maximize business value and productivity while achieving the highest ROI is crucial. This presentation will explore how integrating the Software Development Lifecycle (SDLC) with the principles outlined in Marty Cagan's seminal works (Inspired: How to Create Tech Products Customers Love and Empowered: Ordinary People, Extraordinary Products) can revolutionize data product development. By leveraging Cagan's methodologies, which emphasize customer-centric design, cross-functional collaboration, and agile practices, organizations can create data products that not only meet but exceed customer expectations. 

This session will detail practical strategies for implementing these practices within the SDLC framework, ensuring that data products are both innovative and aligned with business goals. Attendees will gain insights into optimizing product management processes with tools like data observability, fostering a culture of empowerment, and driving continuous innovation to achieve sustainable business success.

Data Practitioners Breakout Track | Pioneering Data Observability

From Monolith to Microservices: Using Data Observability to Build a New Lending Platform

For private banking company Earnest, high-quality, reliable data from end-to-end is absolutely essential. Join Bronte Baer, Manager of Data Platforms & Analytics Engineering at Earnest, as she dives into their transition from a monolithic data system to a microservices-based architecture and addresses the challenges of data migration, joining, monitoring, and validation in a new, decentralized environment.

She’ll share real strategies for leveraging data observability and metadata cataloging to ease the pain of a migration and how those strategies ultimately helped her team build a more reliable lending platform.

Data Practitioners Breakout Track | Pioneering Data Observability

From the Experts: Building the Blueprint for AI-Ready Data

With data and AI reshaping industries, the need for reliable, high quality data is business critical. But, how are data teams actually driving data quality and reliability in practice?  

We’re gathered a quorum of data leaders from SurveyMonkey, Grammarly and DraftKings to share how they’re tackling data quality head on. Tune in to learn best practices and lessons learned for how to approach implementing data quality management processes, technologies, and organizational changes to ensure their company can fly high with reliable data.

Data Leaders Breakout Track | Leading with Data + AI

Operationalizing Data Reliability in the Age of Generative AI

Earlier this year, Monte Carlo introduced the Trusted Data for AI (TDAI) Customer Advisory Council - an exclusive group of top technology leaders whose aim is to make the data powering AI more trustworthy and reliable. 

In this special IMPACT session, hear from three TDAI Council members to get their blueprint for how they’ve fully embraced and operationalized data observability to drive their AI strategies at their organizations.

Closing Keynote Speaker | Main Stage

Going for Gold: A Conversation with U.S. Gold Medal Olympian Allyson Felix on Breaking Barriers with Data

We have an exciting surprise in store for you! A special guest, widely regarded as one of the greatest of all time at their craft, will be joining us. This legendary figure has dominated the global stage, winning numerous medals and using groundbreaking data-driven techniques to enhance their performance.

In a rare and exclusive conversation with Monte Carlo CEO Barr Moses, our mystery guest will dive into how data shaped their journey to the top, how AI is transforming the world, and the vital role of data in advocacy. You won’t want to miss this captivating session—stay tuned for the big reveal!