How to streamline data science and feature creation workflows in Snowflake

Simon Field
SnowCAT Technical Director
Daniel Gray
VP, Solutions Engineering

Watch this Tech Talk to learn how to use AtScale and Snowflake to streamline time series predictions and move machine learning models closer to your data.

Now available on-demand!

Learn about driving data science workloads to Snowflake using the AtScale semantic layer to eliminate data engineering, accelerate time to prediction, and streamline the management of ML feature stores (“feature engineering”).

Our featured speakers will walk you through an end-to-end demo based on a Credit Card Fraud detection use case to illustrate using Snowflake and AtScale to simplify and accelerate feature creation workflows and embed machine learning models.

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In this Tech Talk

You will learn about using:

  • AtScale’s semantic layer to enable data, features and relationships to be modeled over Snowflake tables and how to expose business impact of predictions
  • Snowpark to enable Data Engineers and Scientists to build data engineering pipelines and execute models for more automated time series feature creation
  • Materialized Views to create repository of ML features used for training (scikit-learn) and prediction with feature write-back from AtScale to Snowflake
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Who should watch

Data science and AI leaders and practitioners (e.g., Chief Data Officers, data scientists, and analytics professionals) who want to better understand how Snowflake’s Data Cloud and AtScale’s Semantic Layer can improve data science workflows. 


Simon Field
SnowCAT Technical Director

Simon works in Snowflakes Customer Acceleration Team (SnowCAT), supporting customers to utilise new and advanced product capabilities within Snowflakes Data Cloud to improve the value they derive from their data. Simon has worked in the field of Advanced Analytics, Data Warehousing, Big Data and Data Science for over 30 years, helping organisations make the transition to data-driven decision making.

Daniel Gray
VP, Solutions Engineering

Daniel Gray brings rich experience in technical solutions engineering as well as software engineering to his work with global enterprise organizations. Prior to joining AtScale to lead the Solutions Engineering team, Daniel spent many years in the analytics space including Hewlett-Packard’s Advanced Technology Center, Vertica, and Domino Data Lab. When he’s not in the office or onsite with customers, you’ll find Daniel running, climbing, hiking, and biking – basically anything outdoors.