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Coalesce raises more funding to transform data for Snowflake customers

Data transformation and optimization—tasks that many, if not most, large enterprises handle—are not easy. But the challenges appear to be growing thanks to huge developments in artificial intelligence and cloud technology. In a recent Gartner survey, less than half (44%) of data and analytics leaders said their teams are able to effectively deliver value to their organizations, not because of a lack of trying, but because of resources, funding and proficiency Not enough staff.

Armon Petrossian and Satish Jayanthi encountered these obstacles at data automation company WhereScape. There, the two were responsible for solving data warehousing problems for WhereScape’s customers. (Petrossian is the national sales manager and Jayanthi is the senior solutions architect.) After working at WhereScape for about six years, Petrossian and Jayanthi came to believe they could do a better job at data transformation and issues related to data optimization. –very worried.

The result is Coalesce, a San Francisco-based company that develops a suite of data transformation services, applications and tools. Coalesce on Thursday announced the closing of a $50 million Series B round co-led by Industry Ventures and Emergency Capital, bringing the startup’s total funding 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 most of their time on data preparation, which includes data cleaning and transformation, manual coding, and building data pipelines to get data from source to dashboards or other business uses. These manual processes are very time-consuming , labor intensive, and most importantly, not scalable.”

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

Coalesce responded by building a platform that could standardize data while automating the more repetitive and mundane data transformation processes. Petrossian said that by using Coalesce, data science teams can leverage metadata to manage transformations while understanding how different data are linked and connected.

“As a company’s data grows, so does the complexity of the data pipelines and data models that need to be built and maintained so that the data is trustworthy and produces accurate insights and decisions,” he said. “So scalability is critical for enterprises, and our product delivers exactly that. By automating the data transformation process, we enable data engineers to build data pipelines faster and more efficiently, ultimately reducing costs and Time to value for your organization’s data. “

Coalesce is built specifically for use with Snowflake’s data cloud offering; not surprisingly, Snowflake Ventures, Snowflake’s corporate venture capital arm, is an investor.

This vendor lock-in could hinder expansion, especially given that Coalesce is not the only provider of data transformation tools. Dbt and even traditional extract, transform, and load tools like Informatica and Talend can be considered competitors. Then there are upstarts like Prophecy, which last October raised $35 million from venture capital firms Insight Partners and SignalFire.

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Coalesce provides a range of settings and configurations for organizing and normalizing data in a Snowflake environment. Image Source: merge

But Petrossian says that’s not the case.

“The Series B round will allow us to become a profitable company if we choose to do so,” he said. “Our company was born during the pandemic, which gave us the opportunity to focus on ‘secretly’ building a product that served Fortune 500 companies that were able to withstand what was then a potentially looming economic downturn. Overall, this audience Being more adaptable to economic changes makes our products and business more adaptable to market headwinds.”

In Petrossian’s view, Coalesce has “multiple” (Mom said exactly how many) Fortune 500 customers and has seen recurring revenue grow 4x year-over-year in the fiscal year ending in January 2024. Coalesce plans to expand its 80-person team to about 100 by the end of this year.

Petrossian hinted in no uncertain terms that generative AI and machine learning applications could become a multiplier for Coalesce’s business.

“We often hear from customers that their executive leadership asks about AI and large language models, and they have to lay the foundation for the conversation by explaining why they need to make sure they have the appropriate data foundation in place in the first place,” he said, pointing specifically to generative artificial intelligence. The field of intelligence continues to grow rapidly. “That’s where we come in. Our mission is to fundamentally improve the analytics environment by making enterprise-scale data transformation as efficient and flexible as possible so organizations can quickly implement and leverage advanced use cases such as artificial intelligence, machine learning and generative artificial intelligence Intelligence. Simply put, we believe the value of Coalesce’s technology is an inevitable catalyst to support the scalability and governance required for future cloud computing.”

In addition to the industrial and emerging sectors, 11.2 Capital, DNX Ventures, GreatPoint Ventures, Hyperlink Ventures, Next Legacy Partners, Snowflake Ventures and Telstra Ventures participated in Coalesce’s Series B funding round.

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