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Over the last year, Snowflake has worked aggressively to expand its data cloud. The Montana-based company has been focusing on building machine learning extensibility into the platform, and with this deal, it has taken a step in this direction.
What does Myst bring to the Snowflake?
Myst offers an AI platform that provides data science teams with a workflow to build, deploy and maintain highly accurate forecasting models on time series data in minutes.
Time series data, also called time-stamped information, is a sequence of data points indexed over a specific period of time. These data points consist of successive measurements made from the same source — stock price movement over the years, for instance. With this deal, which will see Myst’s team join Snowflake, the latter is expected to advance its data cloud with time-series forecasting capabilities, ultimately enabling teams to use their historical data to look ahead.
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“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,” Greg Czajkowski, SVP of engineering at Snowflake, said in a blog post.
The application of time series forecasting spans across industries, he added.
Snowflake quiet on specific details
While Snowflake has not shared the specific details of the acquisition, such as when it will close or how the integration into the data cloud will take shape, the deal certainly reinforces the company’s commitment to the data science community. In all, Snowflake currently supports eight workloads: data warehouse, data lake, data engineering, data apps, data sharing, data science, unistore and cybersecurity.
Prior to this, the company had acquired document understanding platform Applica and open source app framework Streamlit. It has over 7,000 enterprise customers.
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