Tech

Coalesce raises more cash to transform data for Snowflake customers

Data transformation and optimization, tasks faced by many, if not most, large companies, are not easy. But thanks to the enormous growth of AI and cloud technologies, the challenges appear to be growing. In a recent Gartner survey, less than half (44%) of data and analytics leaders said their teams are effective at delivering value to their organization, not for lack of effort, but because of ‘a lack of resources, financing and qualified personnel.

Armon Petrossian and Satish Jayanthi encountered these blockers at WhereScape, the data automation company. There, the two men were responsible for solving data warehousing problems for WhereScape customers. (Petrossian was the national sales manager and Jayanthi was a senior solutions architect.) After spending about six years at WhereScape, Petrossian and Jayanthi came to believe they could do one (or two) better when it came to transformation data – and issues related to data optimization. – were concerned.

The result was Coalesce, a San Francisco-based company building a suite of data transformation services, applications and tools. Coalesce announced Thursday that it has closed a $50 million Series B funding round co-led by Industry Ventures and Emergency Capital, bringing the total raised by the startup to $81 million.

“The data transformation layer has long been the biggest bottleneck in analytics,” Coalesce CEO Petrossian told TechCrunch. “Data science and engineering teams spend the majority of their time on data preparation, which includes data cleaning and transformations, hand coding, and creating data pipelines to route data from source to dashboard or other commercial uses. These manual processes are time-consuming, labor-intensive, and most importantly, not scalable.

The data supports Petrossian’s claims. A 2020 survey by Anaconda, the data science tools provider, found that data scientists spend nearly half (45%) of their time on data preparation tasks, including loading and data cleaning.

Coalesce’s answer is a platform that standardizes data while automating the most repetitive and mundane data transformation processes. With Coalesce, data science teams can use metadata to manage transformations by understanding how different data is related and connected, Petrossian says.

“As an enterprise’s data grows, so does the complexity of the data pipelines and data models that must be built and maintained for the data to be reliable and result in accurate insights and decisions,” he said. he declared. “So scalability is of critical importance to businesses, and that’s exactly what our product delivers.” By automating data transformation processes, we enable data engineers to build data pipelines faster and more efficiently, thereby reducing costs. And the time to value for the organization’s data.

Coalesce is designed to work exclusively with Snowflake’s Data Cloud product; Unsurprisingly, Snowflake’s corporate VC arm, Snowflake Ventures, is an investor.

This type of vendor lock-in could be anathema to expansion, especially since Coalesce isn’t the only data transformation tool provider in town. Dbt and even legacy extract, transform and load tools like Informatica and Talend could be considered competitors. There are also newcomers like Prophecy, which last October secured a $35 million investment from venture capital firms Insight Partners and SignalFire.

Coalesce offers a range of settings and configurations for organizing — and normalizing — data in a Snowflake environment. Image credits: Melt

But Petrosian says that is not the case.

“Series B puts us in a position to become a profitable company if we want to,” he said. “Our company was born during the pandemic, which gave us the opportunity to focus on creating a ‘stealth’ product that would serve Fortune 500 companies that were resilient to the potential looming recession at the time. This audience is more resilient to economic changes in general, which makes our products and businesses more resilient to market headwinds as well.

To echo Petrossian’s point, Coalesce has “several” (mom says exactly how many) Fortune 500 customers and recurring revenue that grew 4x year over year during the fiscal year ending in January 2024. As it focuses its efforts on improving the Coalesce platform. performance, introducing AI features and reaching out to existing Snowflake customers, Coalesce plans to expand the size of its team from 80 people to around 100 by the end of the year.

Petrossian hinted, not so subtly, that generative AI and machine learning applications could be force multipliers for Coalesce’s business.

“Our customers often tell us that their leaders ask them about AI and big language models, and they need to support that conversation by explaining why they need to make sure they have the foundation in the first place of appropriate data in place,” he said, noting in particular the continued meteoric growth of the generative AI sector. “This is where we come in. Our mission is to radically improve the analytics landscape by making enterprise-wide data transformations as efficient and flexible as possible, so organizations can quickly move to implement and leverage advanced use cases such as AI, machine learning and generative AI. In short, we see the value of Coalesce’s technology as an inevitable enabler to support the scalability and governance needed in the future of cloud computing.

Beyond industry and emergence, 11.2 Capital, DNX Ventures, GreatPoint Ventures, Hyperlink Ventures, Next Legacy Partners, Snowflake Ventures and Telstra Ventures participated in Coalesce’s Series B round.

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