Customers Share Their Machine Learning Success Stories in the Data Mastery Tour

The most important factor to successful machine learning is having the right data at scale, but organizations struggle with how to get the right datasets combined into the right format for their projects. At Databricks, we've seen customers achieve success by bringing data and ML together, and we've partnered with Snowflake to share their stories across the country in a series we are calling the Data Mastery Tour.

The Data Mastery Tour is a great way for data engineers, data scientists and business analysts to learn how to unify data with machine learning. In many cities along the tour, customers will share how they followed this approach with the Databricks Unified Analytics Platform and the Snowflake Cloud Data Warehouse, and how's that's driving their machine learning success.

Plano TX (2/19/19)

Paul Bruffett is an Enterprise Information Architect at Devon Energy, an American independent natural gas, natural gas liquids, and petroleum exploration company focused on onshore exploration and production in North America. Paul will speak on how efficient data pipelines are driving proven and quantifiable machine learning use cases around parts maintenance, supply chain management, and intrusion detection at Devon Energy.

Chicago IL (2/20/19)

Hanna Torrence is a Data Scientist at ShopRunner, leading a team that leverages e-commerce data from a network of over 140 retailers to build personalization products for ShopRunner's 6 million members. She will speak to how efficient data pipelines are driving proven and quantifiable machine learning use cases around personalization, recommendations, targeting, and analysis of text and images.

Boston MA (2/26/19)

Megan Wellons is an Associate Data Scientist at Rue Gilt Groupe, a premier off-price e-commerce portfolio company that connects more than 20 million members. She will speak to how efficient data pipelines are driving proven and quantifiable machine learning use cases around personalization, recommendations, and targeting.

The sessions will also include an in-depth demo that illustrates how to streamline data pipelines and apply them to machine learning use cases. Join us at these upcoming Databricks events to learn more.