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Data Observability Provider Monte Carlo Raises $135M, Boosts Valuation To $1.6B

The data observability platform developer is seeing rapidly growing demand as data volumes grow, data use cases expand and businesses and organizations staff up their data teams.

Monte Carlo, a leading data observability and reliability software startup, has raised $135 million in a Series D round of funding, financial resources the company will use to accelerate product development and expand its geographic and vertical industry sales and marketing efforts.

With this round Monte Carlo said it has achieved a $1.6-billion valuation. The San Francisco-based company has raised $236 million in just over the last 20 months, including a $60-million Series C round in August.

The latest funding round was led by IVP with participation from Accel, GGV Capital, Redpoint Ventures, ICONIQ Growth and GIC Singapore.

[Related: The Coolest Data Management And Integration Software Companies Of The 2022 Big Data 100 ]

Monte Carlo develops a machine learning-based data observability platform that provides a comprehensive view of the health and reliability of an organization’s data.

The company’s software is part of a broader data observability category of software platforms and tools that is one of the fastest growing segments of the big data space.

By making data more reliable and actionable, Monte Carlo’s software reduces system downtime and the costs of poor-quality data while improving the outcomes of data use cases such as business analytics. The company pointed to a 2021 Gartner report that said poor data quality costs businesses and organizations an average of $12.9 million per year.

Monte Carlo has more than doubled its revenue each quarter since August of last year and recorded 800 percent growth in revenue year over year, said Lior Gavish, Monte Carlo co-founder (pictured), in an interview with CRN. Over the past 20 months the company has grown from 20 employees to 120 and in just the last six months has attracted such customers as JetBlue, CNN, Affirm and SoFi.

“If you’re doing anything with data, observability is a must-have,” Gavish said. “The dependence on data, the criticality of having the right data and trusted data at all times, is increasing.”

Data Staff Need Reliable Data

As data-intensive systems and processes become more mission-critical, businesses and organizations are staffing up with data professionals for whom data reliability is key. “That’s where data observability comes in. We see, across the board, our customers are doubling down on their data teams, hiring data scientists, data engineers [and] data analysts,” Gavish said.

“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, in a statement.

Monte Carlo will invest the new funding across a number of operational areas within the company, Gavish said. That includes continued development of the company’s platform and extending its data observability capabilities to a wider range of data systems and IT including data lakes, data orchestration tools and data streaming systems.

The company also plans to expand its go-to-market efforts, including in key verticals such as ecommerce, financial, insurance, retail and media, and expand its presence in Europe/Middle East/Africa (EMEA).

“As companies continue to invest in technologies that drive smarter decision making and power digital services, the need for reliable, actionable data has never been higher,” said Cack Wilhelm, General Partner at IVP, in a statement. “Monte Carlo is charting the path forward for the data observability category and setting a precedent for the future of the modern data stack. 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.

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