Snowplow, the industry leader in data creation and behavioral data, today announced an enhancement to its behavioral data platform to accelerate machine learning. Announced at the 2022 Snowflake Summit in Las Vegas, Snowplow’s behavioral data platform can now feed AI-ready, rich, accurate and complete data directly into artificial intelligence and machine learning models, without any major data preparation bottlenecks.
Snowplow enables organizations to create and consume AI-ready, high-quality behavioral data, which significantly reduces the time data science teams spend on data cleaning and wrangling as they prepare their data sets for AI and ML projects. Now, data can hit the warehouse or lake quickly and be instantly ready for action, allowing businesses to capitalize on their behavioral data securely and at scale.
The announcement comes shortly after Snowplow joined the Snowflake Partner Network as a Premier Partner and achieved Snowflake Ready Technology Validation. The new partnership between the two companies brings a digital analytics solution to joint customers, who are encouraged to learn more about its benefits at Summit.
With Snowplow’s AI-ready data and integration with Snowflake, the Data Cloud company, joint customers can compete with tech giants whose teams have leveraged AI-ready datasets for years. The combination of Snowplow’s ability to generate, enhance and model AI and ML-ready behavioral data with Snowflake’s Data Cloud capabilities provides businesses with a single platform on which they can power advanced analytics and develop a deeper understanding of their users.
Alongside the Snowflake-powered Advanced Analytics, joint customers can also benefit from the Propensity to Engage solution which utilize the pre-trained ML models in Snowflake’s Snowpark. Snowpark is transformative for data programmability and can improve developer efficiency in creating and operationalizing pipelines at scale, from Snowflake’s single, integrated platform. The Propensity to Engage solution identifies how likely users are to engage with a company, for example make a purchase or request a demo, and returns a score. This is then segmented into three main categories based on propensity and sent to Streamlit, an open-source app, for further analysis.
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Many leading data brands, including the world’s most popular platform for athletes, Strava, have already trusted Snowplow to solve their most complex data challenges and are already taking advantage of Snowplow’s AI-ready behavioral data. Daniel Huang, data engineering manager at Strava said: “The rich and complete data we get at Snowplow helps us unlock more comprehensive and complex analysis to better understand how athletes in our community are utilizing our platform. Since implementing the technology, we have gained wider and deeper data coverage across various business areas. Data has become an integral part of our product development and company as a whole. We hope to further embrace ML-driven products and derive more value from the user behavior we track for years to come.”