We’re excited to share that Monte Carlo has raised $16M in funding to pioneer the Data Reliability category. Our Series A was led by Accel, with participation from GGV Capital, and enables us to pursue our mission of accelerating the world’s adoption of data by reducing Data Downtime. Other angel investors include DJ Patil, the former Chief Data Scientist for the U.S. as well as top executives from Cloudera, eBay, Google and VMWare. As part of this news, we are excited to share that Steve Loughlin, Accel, has joined Monte Carlo’s Board of Directors.
As businesses increasingly rely on data to drive better decision making and maintain their competitive edge, it’s mission-critical that this data is accurate and trustworthy. After talking with over hundreds of data leaders across the space, Monte Carlo estimates that data teams spend north of 30 percent of their time tackling data issues, distracting data engineers, data scientists, and data analysts from working on projects that actually move the needle. In the same way that New Relic, DataDog, and other Application Performance Management (APM) solutions ensure reliable software and keeps application downtime at bay, Data Reliability solves the costly problem of broken data pipelines and Data Downtime by delivering full, end-to-end Data Observability.
Monte Carlo has built the first end-to-end platform for enterprises to increase trust in data and eliminate Data Downtime, in other words, times when data is inaccurate, missing, or otherwise erroneous. Our 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. Companies like Compass, Eventbrite, Mindbody, Yotpo, and Hippo rely on us today so that data can better inform their decision-making and business strategy.
“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. With strong customer adoption among major brands since day one and an impressive waitlist, it’s clear that Monte Carlo is leading the way in creating a new category around data reliability that the industry has been waiting for. Monte Carlo is the leading Data Reliability platform today.” – Steve Loughlin, Partner, Accel and Monte Carlo board member
Addressing the limitations of data-driven decision making
You may be wondering why teams need reliable data in the first place, and it all comes down to how companies use data to make important business decisions. Data-driven decision making is a concept that’s been around for decades, but only recently has it become actionable (and practical) for the average business. Teams now have access to unlimited amounts of information, plus the tools needed to draw insights from it all, but if you can’t trust your data, all of these insights are for naught.
As the number of data sources increase and data becomes more accessible to a wider range of users, often in real-time, downtime and mistakes are inevitable. When you’re basing big decisions or strategies on this information, this can be detrimental. In June 2020, for instance, it was reported that bad data hampered the U.S. government’s ability to roll out its COVID-19 economic recovery programs. In addition to other errors, this data downtime incident sent over $1.4 billion in COVID-19 stimulus checks to dead people. And this is just one example of what happens when data downtime strikes.
In my previous role as the VP of Customer Operations at Gainsight, I worked with Fortune 500 companies to help teams use data as a competitive advantage. I was struck by the fact that there were so many great solutions available to identify and resolve software reliability and observability issues, but nothing to measure the health of data and ensure reliability. Like so many other companies, we had no easy way to guarantee the validity of information flowing through pipelines. Oftentimes, technical resources would need to be redirected to try to build their own custom solutions, which means less time to focus on business priorities.
“Data-driven decision making is a huge priority for Mindbody, but our analytics are only as reliable as the data that informs them. We are working with Monte Carlo to monitor and alert for abnormalities in the data life cycle, such as null values and duplicate data, that would otherwise go unnoticed until it’s too late. By partnering with Monte Carlo, my team can achieve full Data Reliability across our pipelines,” – Alex Soria, VP of Data & Analytics, Mindbody
In the coming months, we look forward to continuing to build the Data Reliability movement and enabling it with a new category of products that help businesses grow and achieve their ambitions by working with more reliable data to make better decisions.
If you’re interested in learning more about how we can help your company, join our waitlist. Teams can get up-and-running in minutes, as our no-code implementations automatically work with any existing cloud stack.