Headquartered in Montana, Snowflake employs over 5,000 staff in around 30 offices globally. Companies use its data cloud to combine and share data, and undertake analytics work. 

Myst, founded in 2018, offers an artificial intelligence-based data analysis platform that is used to forecast electricity demand and supply. The platform allows data teams to build, deploy, and maintain forecasting models using time series forecasting.

Snowflake announced its intent to acquire Myst in a post on its website, adding that it would “bring the Myst team into Snowflake in order to continue advancing our platform”. The terms of the deal have not been disclosed.

Time series forecasting can be applied across a range of scenarios, including forecasting public health outcomes, predicting product demand and forecasting increases in energy costs.

Greg Czajkowski, senior vice-president of engineering at Snowflake, wrote in the post: “Time series forecasting is one of the most applied data science techniques in business. It is used extensively in supply chain management, inventory planning, and finance. Accurate forecasts can establish measurements to guide management, facilitate planning and goal setting, and help mitigate risk.”