I’m excited to share that Monte Carlo has raised $60 million in Series C funding from ICONIQ Growth with participation from Salesforce Ventures and existing investors Accel, GGV Capital, and Redpoint Ventures – bringing our total funding to $101M. With this round, we will fuel the growth of the Data Observability category, further develop our product offerings to better serve our customers, support more use cases, and expand to new markets.
Our Series C establishes us as the first Data Observability company to reach this milestone, a testament to our team’s industry-defining thought leadership, new product releases, and rapid customer growth.
The rise of data downtime
In 2021, it’s simply not enough to use data to drive accurate decision making and power digital products — you need to trust it, too. If you’ve been on the receiving end of bad data, you understand the pain: lost revenue, wasted time, and most importantly, lost confidence in data products. Once trust is lost, it’s hard to gain back.
According to a recent report from Gartner, data teams spend millions of dollars per year and 40 percent of their time tackling poor data quality, a number only expected to increase as companies become more data-driven. Simultaneously, data systems are becoming more complex, distributed, and decentralized, widening the gap for data downtime – periods of time when data is missing, erroneous, or otherwise inaccurate, at each stage of the data lifecycle.
As first defined by the team here at Monte Carlo, Data Observability leverages the best practices and principles of automatic application observability (think: Datadog or AppDynamics) and applies them to data pipelines, giving data engineers and analysts visibility across all data pipelines and data products. Simultaneously, Monte Carlo’s machine learning-powered platform provides data leaders and other data stakeholders with a holistic view of their company’s data health and reliability for critical business use cases.
“In partnering with both Snowflake, the category creator in cloud data warehousing, and Datadog, the leader in application observability, we have witnessed firsthand how the power of innovative approaches to longstanding problems can transform industries and improve business outcomes. The issue of data downtime has been around for decades, but Monte Carlo is innovating in data reliability, bringing data teams a powerful solution to truly solve this hundred billion-dollar problem,” said Matt Jacobson, General Partner at ICONIQ Growth. “We believe the potential impact of this technology is enormous and Monte Carlo is blazing the path forward for the Data Observability category.”
As the industry leader in Data Observability, Monte Carlo solves this problem by enabling teams to accelerate the adoption of trustworthy, reliable data and stop bad data in its tracks — before it impacts the business. Our investment from ICONIQ Growth and other leading VCs signals the market confidence in our category and the need for a new approach to solving the very real problem of data downtime.
Category leadership, company expansion, and customer growth
Since our Series B announcement in February 2021, we have more than doubled our revenue quarter-over-quarter, with an 800 percent increase in revenue year-over-year. Since the start of 2021, we have brought on new customers across industries, including Intuit, Affirm, Fox, Vimeo, PagerDuty, and Zalora, among others. Additionally, we are the first Data Observability company to partner with industry leaders Snowflake, Looker and PagerDuty, bringing automatic, end-to-end data monitoring, anomaly detection, and field-level lineage to data teams everywhere. We’re honored to work with companies who are forging the path towards data reliability, the first step towards accelerating the adoption of data at scale.
My favorite part of this journey? Working with our awesome customers to pioneer this category and help them achieve truly reliable data:
“Powered by real-time data, PagerDuty’s Digital Operations management platform enables over 16,800 businesses across the world to manage urgent, mission-critical work and keep digital services always on. When it comes to ensuring the uptime of PagerDuty’s business data, our Data Engineering & Business Insights team applies similar principles of AI-driven observability and monitoring to stop data quality issues in their tracks. With Monte Carlo, my team is the first to know when data breaks so that we can manage that incident lifecycle through PagerDuty, in turn allowing us to prevent and resolve data downtime before it impacts the business,” said Manu Raj, Senior Director of Data Platform and Analytics at PagerDuty.
“To power product growth and deliver exceptional user experiences across our suite of insurance offerings, we partnered with Monte Carlo for automatic, end-to-end Data Observability. Within minutes, we were up and running with Monte Carlo and within days, the platform was uncovering critical schema and pipeline changes that would have impacted the business if left undetected,” said Matt Frazier, Chief Analytics Officer at Pie Insurance.
“With Monte Carlo, my team can understand what data is important for the business, as well as whether or not this data can be trusted. Monte Carlo’s end-to-end lineage helps me draw these connections between critical data tables and the reports the company relies on to make decisions and power our product roadmap,” said Satish Rane, Head of Data Engineering, ThredUp.
And the list goes on…
For more insights, register for the industry’s first Data Observability Summit: IMPACT: The Data Observability Summit, featuring keynotes from data leaders including:
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