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Data Observability Tech Startup Monte Carlo Raises $60M

Monte Carlo’s platform is designed to help businesses monitor and improve the quality and reliability of their data assets as they become data-driven organizations.

Monte Carlo, a startup developer of data observability software, has raised $60 million in Series C funding, financing the company will use to accelerate product development, fuel its go-to-market efforts and promote the data observability concept.

The new funding announced Tuesday is Monte Carlo’s third in less than a year – including funding rounds in September 2020 and in February of this year – that bring the San Francisco-based company’s total financing to $101 million.

The funding round was led by ICONIQ Growth with participation from Salesforce Ventures and existing investors Accel, GGV Capital and Redpoint Ventures.

[Related: Emerging Big Data Vendors To Know In 2021]

Monte Carlo’s data observability software is used to monitor data across IT systems, including in databases, data warehouses and data lakes, to gauge and maintain data quality, reliability and lineage – what the company calls “data health.”

“The problems of bad data [and] data downtime have been around for a while. But the impact of that has been exacerbated in the last few years as companies actually become data-driven,” said CEO and co-founder Barr Moses in an interview with CRN.

Moses noted that today data is being used by a greater number of people throughout businesses and organizations and they are using data for a wider range of applications and decision-making tasks. And unlike the past when an organization’s data resided in a limited number of systems, data today is disbursed cross many databases, operational systems, data warehouses and data lakes – on-premises and in the cloud.

Businesses have made huge investments in data management and data analytics technologies to become data-driven enterprises. “But the data itself is often wrong, inaccurate and can’t be trusted,” Moses said.

With the aim of improving data quality and eliminating data downtime, Monte Carlo’s data observability technology applies to data sources and pipelines similar practices used in DevOps, including automated monitoring, alerting and triaging, to evaluate data quality and identify problems. The system monitors data in the same way application performance monitoring (APM) tools like New Relic, Datadog and Cisco AppDynamics monitor applications and identify problems.

Monte Carlo’s platform evaluates data according to its freshness and how up-to-date it is, the volume or completeness of data tables, the data schema or organization of the data, data lineage including sources and usage, and the data’s distribution (whether the data’s values are within an accepted range).

“We’re really filling the data visibility and observability gap. So, we can tell you when things are broken and help you find the root cause,” said Lior Gavish, Monte Carlo co-founder and head of engineering, in the interview.

Monte Carlo, founded in 2017, will apply the additional funding to expanding its product development and go-to-market activities and helping its customers get full value out of the software. Moses said some of the funding will be used to promote the relatively new data observability concept.

“The ability to automatically see data health, data quality, lineage, meta data – all that information in one platform – that is very unique,” Moses said of Monte Carlo’s offering.

The company today is largely working directly with its mid-market and enterprise customers, including Fox, AutoTrader and Heart, Moses said. But it has begun to explore working with systems integrators, strategic service providers and data consultants as it expands its sales efforts.

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