Coalesce Debuts From Stealth, Attracts $5.92M for Analytics Platform

Data management company Coalesce this week emerged from stealth with the launch of the Coalesce Data Transformation platform. Coalesce aims to simplify the modelling, cleansing, governance, and documentation of data by analytics efficiency and flexibility.

Coalesce also announced it has raised $5.92 million in seed funding which was led by 11.2 Capital and GreatPoint Ventures. Those funds will be used to advance the Coalesce platform while growing sales, marketing, engineering functions, and go-to-market strategy.

“The largest bottleneck in the data analytics supply chain today is transformations. As more companies move to the cloud, the weaknesses in their data transformation layer are becoming apparent,” said Armon Petrossian, the co-founder and CEO of Coalesce. “Data teams are struggling to keep up with the demands from the business, and this problem has only continued to grow with the volumes and complexity of data combined with the shortage of skilled people. We are on a mission to radically improve the analytics landscape by making enterprise-scale data transformations as efficient and flexible as possible.”

“Built from a team with deep data automation knowledge and expertise, Coalesce is solving the most pressing challenges that come with maintaining and transforming large enterprise data warehouses,” said Shelley Zhuang, the founding partner of 11.2 Capital. “Our investment is a testament to the intuitive nature of the Coalesce Data Transformation platform.”

“Since the early days of data warehousing, companies have struggled to transform and optimize data properly for consumption. With the enormous growth of the cloud, that challenge has only increased,” said Ray Lane, the managing partner of GreatPoint Ventures and a former president and chief operating officer of Oracle. “We see the value of Coalesce’s technology as an inevitable catalyst to support the scalability and governance needed for cloud computing.”

Coalesce is designed with column-aware architecture which facilitates the deployment of reusable data patterns and change management at scale. Curated packages with best-practice templates are also available.

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