Dataform scores $2M to build an ‘operating system’ for data warehouses
Dataform, a U.K. company started by ex-Googlers that wants to make it easier for businesses to manage their data warehouses, has picked up $2 million in funding. Leading the round is LocalGlobe, with participation from a number of unnamed angel investors. The startup is also an alumni of Silicon Valley accelerator Y Combinator and graduated in late 2018.
Founded by former Google employees Lewis Hemens and Guillaume-Henri Huon, Dataform has set out to help data-rich companies draw insights from the data stored in their data warehouses. Mining data for insights and business intelligence typically requires a team of data engineers and analysts. Dataform wants to simply this task and in turn make it faster and cheaper for organisations to take full advantage of their data assets.
“Businesses are generating more and more data that they are now centralising into cloud data warehouses like Google BigQuery, AWS Redshift or Snowflake. [However,] to exploit this data, such as conducting analytics or using BI tools, they need to convert the vast amount of raw data into a list of clean, reliable and up-to-date datasets,” explains Dataform co-founder Guillaume-Henri Huon. .
“Data teams don’t have the right tools to manage data in the warehouse efficiently. As a result, they have to spend most of their time building custom infrastructure and making sure their data pipelines work”.
Huon says Dataform solves this by offering a complete toolkit to manage data in data warehouses. Data teams can build new datasets and set them to update automatically every day, or more frequently. The entire process is managed via a single interface and setting up a new dataset is said to take as little as 5 minutes. “On top of this, we have an open source framework that helps managing data using engineering best practices, including reusable functions, testing and dependency management.
Meanwhile, Dataform says the seed funding will help the company continue to grow both its sales and engineering teams. It will also be used to further develop its product. The startup generates revenue based on a classic SaaS model: typically charging per number of users.