Over the past few decades, data-driven decision making has become foundational to the modern enterprise, enabling companies to drive innovation and maintain their competitive edge. Not surprisingly, businesses are investing in the latest data solutions, from cloud warehouses to real-time analytics dashboards, with the big data market expected to be worth a staggering $229.4B by 2025.
As the number of data sources increase and data becomes more accessible to more users, broken data pipelines are unavoidable. In the U.S. alone, companies lose an aggregate $3 trillion per year due to bad data, leading to lost revenue, sleepless nights, and, worst of all, poor decision making.
Monte Carlo is tackling this costly problem by building the world’s first end-to-end Data Reliability platform. In the same way that New Relic, DataDog, and other Application Performance Management (APM) solutions ensure reliable software and keep application downtime at bay, Monte Carlo is the first solution to leverage data observability and eliminate data downtime—a term which Monte Carlo has coined—periods when data is inaccurate, missing, or otherwise erroneous.
When I first met Barr in 2018, I was struck by her tenacity, analytical horsepower, and ability to lead. She had the ingredients to be a world class entrepreneur. Barr’s leadership coupled with Monte Carlo’s stellar team, product, data and security expertise, and a visionary approach to Data Reliability—is why Accel led their Seed and Series A. The market opportunity for the company that solves this problem through full, end-to-end data observability is enormous—and we have our money on Monte Carlo.
Monte Carlo is a game changer for businesses. Just as we invested in PagerDuty to address a critical need for engineering teams to track and report on outages, there’s a need for software that brings together data teams and allows them to collaborate more efficiently and effectively around data downtime. Unlike manual solutions, their category-creating Data Reliability platform uses machine learning to infer and learn your data, proactively identify data downtime, assess its impact, and notify those who need to know. By automatically and immediately identifying the root cause of an issue, teams can collaborate and resolve problems faster.
Today, Fortune 1000 companies and other enterprises like Compass, Eventbrite, and Mindbody rely on Monte Carlo so that their data can better inform their decision-making and business strategy. With such strong customer adoption and an impressive waitlist, I can’t wait to see what their future holds.
—Steve, and the partners at Accel