Monte Carlo: Data Reliability in Every Scenario

August 17, 2021

Story by Matthew Jacobson and Murali Joshi 

In the late 1940s during World War II, computing pioneers John von Neumann and Stanislaw Ulam developed a groundbreaking class of algorithms to improve decision making under uncertain conditions. Called the Monte Carlo Method, the approach made it easier to create powerful models for solving deterministic problems by testing every variable. While von Neumann and Ulam were working on nuclear physics problems, Monte Carlo simulations have since become a universal tool for assessing outcomes and remediating risk in myriad scenarios across science, commerce, finance and engineering. This method’s confluence of thoroughness and real-time iterating makes the technique a trusted and reliable tool for modern data teams. It was only natural that in 2019, when Barr Moses and Lior Gavish were honing their vision to empower the entire data community to realize the full potential of data with end-to-end, real-time trust, they decided to create Monte Carlo. At ICONIQ Growth, we believe modern data teams need data reliability in every scenario and think Monte Carlo is the leading platform to deliver that. We are excited to partner with Barr, Lior and the entire team as they aim to define the category and accelerate the world’s adoption of data by reducing data downtime, in other words, periods of time when data is missing, inaccurate, or otherwise erroneous.

Like its eponym, we think Monte Carlo is fundamentally changing the norms and expectations for data. Its Data Observability Platform enables teams to monitor freshness, volume, schema, lineage, distribution and more critical information about the health of their data as it evolves over time. As most of the world today consumes and generates data at an exponential rate, there exists a growing challenge of managing the complexity, quality and health of this endless set of information. The increasing adoption of cloud data warehouses (Snowflake), data lakes (Databricks), ETL (Fivetran), BI (Alteryx), AI/ML data science (Dataiku), governance (Collibra) and others has set a new foundation for how modern teams analyze, store, extract, load, blend and transform data today. These core infrastructure platforms, individually and collectively, address some critical operational decisions global enterprises make for their businesses. We believe Monte Carlo offers the leading end-to-end observability platform that scales with these growing data infrastructure demands, while maintaining a security-first architecture and instant, no-code onboarding.

This challenge resonates with some of the most influential chief data officers and technology experts around the globe. Prior to Monte Carlo, many of these data professionals were flummoxed that there was no easy way to guarantee the validity of data flowing through pipelines. When Monte Carlo arrived, we often heard descriptors such as “the sky is the limit,” “no-brainer” and “priceless” used to vividly illuminate the importance of the platform and technology. For modern organizations, data reliability in every scenario means saving hundreds of hours per week, reducing data quality issues, increasing analytics ROI, remediating the root causes of broken pipelines and, in turn, accelerating the adoption of data at scale. As its Data Observability Platform continues to observe more and more about an organization’s data behavior and historical patterns, the platform becomes more advanced and enables smarter operational decision-making.

Like the pioneers Ulam and von Neumann, Barr, Lior and the Monte Carlo team are spearheading a powerful mission to accelerate the world’s adoption of data. This resonates deeply with ICONIQ Growth’s focus on channeling capital, talent and ideas to companies that are solving core infrastructure issues for our world. We believe that Monte Carlo combines simplicity and visibility with a deep, technical engine, a marriage that is often seen by several leading data and infrastructure companies that we have partnered with in the past. And now, we are grateful to partner with the company as part of their Series C financing alongside our friends at Accel, GGV Capital, Redpoint Ventures, Salesforce Ventures and others, and thrilled to join Barr, Lior and the entire Monte Carlo team as they seek to bring data reliability in every scenario while helping build the future of data at scale.