Data Transformation and Optimization — Coalesce Solves Enterprise Challenges
Tasks like data transformation and optimization are essential for the success of large enterprises, but they are far from easy. However, with the rise of AI and cloud technologies, these challenges seem to be growing at an alarming rate.
In a recent poll conducted by Gartner, it was found that only 44% of data and analytics leaders feel that their teams are effectively providing value to their organizations. This is not due to lack of effort, but rather a result of insufficient resources, funding, and skilled employees.
“The data transformation layer has long been the largest bottleneck in analytics,” explains Armon Petrossian, CEO of Coalesce, a San Francisco-based company offering a suite of data transformation services, apps, and tools.
Petrossian, along with Satish Jayanthi, encountered these obstacles during their time at WhereScape, a data automation firm where they were responsible for solving data warehousing problems for clients. After spending six years at WhereScape, Petrossian and Jayanthi realized that they could do even better when it came to data transformation and optimization.
Thus, Coalesce was born, with a mission to simplify and streamline the data transformation process for enterprises. And on Thursday, Coalesce announced that it had closed a $50 million Series B funding round co-led by Industry Ventures and Emergency Capital, bringing the total raised to $81 million.
The Need for Coalesce
“Data science and engineering teams spend the majority of their time on data prep, which includes data cleansing and transformations, manually coding and building out data pipelines to get the data from source to dashboard or other business uses,” says Petrossian. “These manual processes are time consuming, labor-intensive, and, most importantly, don’t scale.”
This is supported by data from a 2020 survey by Anaconda, which found that data scientists spend almost half (45%) of their time on data prep tasks, such as loading and cleaning data.
To address this issue, Coalesce offers a platform that standardizes data and automates the more repetitive and mundane data transformation processes. This allows data science teams to use metadata to manage transformations and better understand how different pieces of 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 in order for the data to be trustworthy and result in accurate insights — and decisions,” Petrossian explains. “Scalability is therefore critically important for enterprises, and our product offers just that. By automating the data transformation processes, we enable data engineers to build data pipelines more quickly and efficiently, ultimately reducing costs and the time-to-value of the organization’s data.”
Partnership with Snowflake
To further enhance its capabilities, Coalesce works exclusively with Snowflake’s Data Cloud product. So it comes as no surprise that Snowflake Ventures, the corporate VC arm of Snowflake, is an investor in Coalesce.
Some may worry about the potential vendor lock-in with this partnership, especially with competitors like Dbt, Informatica, and Talend in the market. However, Petrossian reassures that Coalesce is focused on serving its customers and is not hindered by this partnership.
“The Series B puts us in a position to become a profitable company if we were to wish to do so,” Petrossian says. “Our company was born during the pandemic, which gave us an opportunity to focus on building a product while in ‘stealth’ that would serve enterprise Fortune 500 companies that were resilient to the potential looming recession at the time. That audience is more resilient to economic shifts in general, making our product and business more resilient to market headwinds as well.”
In fact, Coalesce already has multiple Fortune 500 customers and has seen a 4x increase in recurring revenue year-over-year in the fiscal year ending January 2024. As it continues to improve its platform, introduce AI features, and reach out to existing Snowflake customers, Coalesce plans to expand its team from 80 to around 100 by the end of the year.
The Future of Coalesce
Petrossian hints at the potential for generative AI and machine learning applications as force multipliers for Coalesce’s business.
“We often hear from our customers that their executive leadership asks about AI and large language models, and they have to ground that conversation by explaining why they first need to ensure they have the proper data foundation in place,” he says. “This is where we come in. We’re on a mission to radically improve the analytics landscape by making enterprise-scale data transformations as efficient and flexible as possible, so organizations can quickly move to implementing and taking advantage of advanced use cases such as AI, machine learning, and generative AI. In short, we see the value of Coalesce’s technology as an inevitable catalyst to support the scalability and governance needed for the future of cloud computing.”
Investors Believe in Coalesce
In addition to Industry Ventures and Emergency Capital, 11.2 Capital, DNX Ventures, GreatPoint Ventures, Hyperlink Ventures, Next Legacy Partners, Snowflake Ventures, and Telstra Ventures also participated in Coalesce’s Series B funding round.
