Monte Carlo Raises $135M Series D to Accelerate the Rapid Growth of the Data Observability Category

Molly Vorwerck

Molly is Head of Content & Communications @ Monte Carlo.

Today, I’m excited to announce that Monte Carlo, the data reliability company, has raised $135M in Series D funding from IVP, with participation from Accel, GGV Capital, Redpoint Ventures, ICONIQ Growth, Salesforce Ventures, and GIC Singapore. With this round, we’ve raised a total of $236M in a 20-month period, most recently announcing their Series C in August 2021 and a suite of new product functionalities to help data teams achieve more reliable data. 

Monte Carlo intends to use the capital infusion to continue improving experiences for its hundreds of customers, scale the data observability category to new verticals, and grow its U.S. and EMEA go-to-market and engineering teams. 

Monte Carlo is now the first data observability company to achieve a billion dollar valuation, joining the ranks of Databricks, Fivetran, Starburst, and dbt Labs as a data unicorn. 

Pioneering the future of data reliability

As companies ingest more data and pipelines become increasingly complex, teams need a way to ensure that the data powering their decision making and digital products is reliable and actionable. 

Mirroring the rise of application performance monitoring (APM) tools like Datadog and New Relic to keep software downtime at bay, data observability solves the problem of data downtime by giving teams end-to-end coverage and visibility into data health across their modern data stack. Monte Carlo’s machine learning-powered platform provides data leaders and other business stakeholders with a holistic view of data reliability for critical business and data product use cases in near real time.

Last year organizations spent $39.2 billion on cloud databases such as Snowflake, Databricks and Google BigQuery, yet Gartner estimates data downtime and poor data quality costs the average organization $12.9M per year. 

Monte Carlo research shows a correlation between data incidents and the amount of data an organization handles, with the average business experiencing at least one data incident for every 15 tables in their environment. 

“As companies continue to invest in technologies that drive smarter decision making and power digital services, the need for high quality data has never been higher. Monte Carlo is charting the path forward for the data observability category and setting a precedent for the future of the modern data stack,” said Cack Wilhelm, General Partner at IVP. “After talking to dozens of Monte Carlo’s customers, two things became crystal clear: they are building a truly incredible product with near-immediate time to value, and they have one of the best teams in data. I’m excited to partner with Barr, Lior, and the rest of Monte Carlo on their vision for data reliability.” 

Category leadership, customer growth and company expansion

Over the past 20 months, Monte Carlo has grown from 20 to 120 people and raised four rounds of funding, signifying the exponential growth of the data observability market and the company at large. With their Series D, Monte Carlo has achieved a $1.6B valuation, a testament to the market enthusiasm for the category and the company’s commitment to making data more reliable for their customers. 

Since their Series C announcement in August 2021, Monte Carlo more than doubled revenue every single quarter and achieved 100 percent customer retention in 2021. Over the past six months, Monte Carlo has brought on new customers, including JetBlue, Affirm, CNN, MasterClass, Auth0, and SoFi, with hundreds of customers paying for and driving value from the platform.

“Over the past several years, companies across industries have gotten more bullish about data than ever before, investing in technologies like Snowflake and Databricks and hiring teams of engineers and analysts to build and scale data products that drive impact for the business. Still, it’s simply not enough to have data – it needs to be discoverable, accessible and reliable,” said Barr Moses, CEO and co-founder of Monte Carlo. “Monte Carlo created the world’s leading data observability platform to accelerate the adoption of reliable data while reducing time to detection and resolution for data downtime. Our customer traction and roster of great partners like Snowflake, Databricks, and dbt Labs highlight  the continued growth and maturation of the data observability category, as well as the industry confidence in Monte Carlo’s approach.” 

Monte Carlo founders Barr Moses and Lior Gavish are writing O’Reilly’s first-ever book on data quality and observability, Data Quality Fundamentals, available for full release in September 2022. The first several chapters of the book are accessible for free, here

To learn how your team can achieve end-to-end data trust, check out our blog, get to know our customers, or request a demo

Companies Pioneering the Data Observability Category With Monte Carlo

JetBlue is New York’s Hometown Airline® and a leading carrier in Boston, Fort Lauderdale-Hollywood, Los Angeles, Orlando, and San Juan. JetBlue carries customers across the U.S., Caribbean and Latin America and between New York and London. 

JetBlue’s data team manages a large variety of real-time and analytical data assets for the airline. Without end-to-end coverage and visibility, the team had to go to extraordinary lengths to fix issues at all times of the day, including weekends and holidays. They even had an “eyes on glass” team manually refreshing dashboards to ensure smooth operations. 

“Data is a key ingredient to maintain the heartbeat of JetBlue’s system operations and customer support centers, ensuring smooth and seamless experiences for travelers throughout our network. With Monte Carlo’s broad coverage and automated lineage, we can be confident our dashboards are accurate without manually monitoring,” said Ashley Van Name, General Manager of Data Engineering, JetBlue. “Our team can identify, prioritize and resolve data issues and any downstream impacts at a much faster rate.”

Gusto’s people platform helps businesses take care of their hardworking teams. Launched in 2012 as ZenPayroll, Gusto serves more than 200,000 businesses nationwide.

The data team needed an automated, end-to-end solution that would alert them to data incidents, but was smart enough to avoid flagging false positives from reconciled tables and hourly schema changes.

“To deliver on our mission of making HR and operations easier and more scalable for growing companies, Gusto needs reliable and trustworthy data, from ingestion in the warehouse to our executive dashboards” said Shanshan Wu, Technical Product Manager, Gusto. “Monte Carlo’s end-to-end data observability has enabled us to have better visibility and deliver better services to our customers. This 10,000-foot view into data health has been a big win for the business.”

tastytrade, Inc. is a leading, US-based trading ecosystem focused on empowering investors through its award-winning financial content, trader education, and tastyworks’ dynamic brokerage services.

Data is a crucial resource to help tastytrade better serve its growing customer base of self-directed traders. Being able to effectively and efficiently harness data enhances tastytrade’s agility and helps them reach their goal of becoming the destination of choice for ambitious investors. 

“Monte Carlo’s ease of use really stood out. It was a huge benefit to have it set up and start working automatically as opposed to having to manage a full infrastructure that would require a full-time data engineer dedicated to it. It’s advantageous to have monitoring, documentation and lineage all wrapped together in the same cohesive UI instead of hopping from tool to tool,” said Alex Welch, Vice President Enterprise Data and Analytics, tastytrade. “A former basketball coach told me, ‘It’s not about going full speed all the time; you need to be able to change speeds at the right place and time.’ And that’s what Monte Carlo and this stack allow. We can move as fast as we want without feeling like we’re being held back by technology, but if something breaks or requirements change, we can pivot if we need to.”

Learn how data observability can help your team achieve highly reliable data by connecting with Molly and the rest of the Monte Carlo team.

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