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Enterprise data observability platform provider Acceldata has raised $50 million in series C funding, as the demand for high-performance data observability continues to grow across enterprises.

Data is key to business success, but an industry-wide effort to exploit so-called Big Data technology using Hadoop and related tooling came up short by many estimates. In operations, growing data and system complexity, combined with the shortage of engineering talent, left teams struggling with failing data pipelines, low-quality datasets and rising data management costs.

“Time and again, strategic data initiatives failed, wasting tens or even hundreds of millions of dollars,” Acceldata CEO Rohit Choudhary told VentureBeat. “The blame always seemed to fall on outdated tools that simply weren’t up to the task of corralling vast amounts of data and transforming signals into actionable intelligence,” he said.

Choudhary saw the phenomenon firsthand in key roles at Hadoop specialist Hortonworks, now part of Cloudera. He said experience showed him how critical it was for enterprises to have a solution to monitor, investigate, remediate and manage their data pipelines across complex systems and decided to launch Acceldata to address the gap. He launched the company in 2018 and was joined by other Hortonworks tech leaders to deliver the data observability that blocked progress for data projects of all sizes.


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What does Acceldata do?

At its core, Acceldata can be described as a multidimensional observability platform that delivers end-to-end visibility into data processing power, data pipeline performance and data quality across modern data stacks. 

The solution looks at all connected data, regardless of source, technology, location or cloud platform, and employs artificial intelligence (AI) and machine learning (ML) to develop better context, learn patterns, and optimize visibility and predictive capabilities over time. It also correlates events to understand the interactions between data, users and applications and to swiftly predict and fix issues like data system performance, lack of resources and cost overruns.

CDOs (chief data officers) can now, in real time, understand potential risks to the business with a holistic lens of data, and make proactive decisions to achieve the right business outcomes,” Choudhary explains. Data engineers can gain full confidence that the data they are using is reliable. Platform and operations engineers can leverage automated recommendations to prevent data outages and maintain 99.99% and better SLAs, he said.

Plans for data observability

Since its launch five years ago, Acceldata claims to have roped in major enterprises, including Oracle, PhonePe, Verisk, Dun & Bradstreet and DBS Bank, as customers. It also supports major data platforms, including Snowflake and Databricks.

With this round of funding, which was led by March Capital, the company’s total capital raised has come close to $100 million. It will use the funds to expand its footprint into the Global 2000 and better compete with other well-funded startups in the observability space, such as Cribl, Monte Carlo and BigEye.

Choudhary said Acceldata sees competition across four categories — data observability, data analytics/catalog/MLops and management, telemetry optimization, and app observability. Players here, he said, include legacy incumbents and emerging startups. But the main competition in the space comes from in-house development teams.

Acceldata’s differentiation, he said, comes via its platform for monitoring not just data and data pipelines, but also the underlying processing compute infrastructure, as well as data access and usage.

The increase in data and the quest for business advantage will continue to spur progress in this area. These needs make observability tools like Acceldata more important than ever for enterprises looking to be data driven. In fact, according to a survey conducted by Censuswide, 80% of enterprise data leaders have already expressed plans to prioritize investments in systems to provide visibility, and 85% plan to deploy data observability in 2023. 

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