A Dataiku and Snowflake Introduction to Data Science
This Snowflake Quickstart introduces you to the basics of using Snowflake together with Dataiku Cloud as part of a Data Science project.
Read the QuickstartDataiku and Snowflake deliver a unique data and AI experience that empowers data and domain experts to build advanced analytics, streamline operations, and ensure visibility and trust in analytics efforts—all on a single, collaborative platform that pushes down workloads to Snowflake for fast, secure, and cost-effective processing and that enables native support beyond SQL to Python, Java, and Scala with Snowpark.
Business and technical users can quickly create and deploy analytics and AI solutions:
Dataiku operates across all industries but is certified with Snowflake competency awards in financial services, healthcare and life sciences, and retail and CPG.
We were able to quickly demonstrate value [from Dataiku and Snowflake] from improved compute and storage capacities across multiple groups so analysts could do their jobs more easily and we could take them off the command line. — Ashish Sharma, Executive Director, Novartis
Read the flyer on how Dataiku and Snowflake work together and deep dive in the integration.
Snowflake and Dataiku TogetherThis Snowflake Quickstart introduces you to the basics of using Snowflake together with Dataiku Cloud as part of a Data Science project.
Read the QuickstartDiscover how Dataiku complements Snowflake to unlock powerful insights, optimize resources, and democratize data analytics. Learn about the perfect duo.
READ THE BLOG POSTIn this brochure, explore how Dataiku and Snowflake work together to bring you the most business value.
READ THE BLOG POSTDiscover the latest Dataiku and Snowflake joint integrations on LLMs and MLOps to reduce time to production from months to just days.
READ THE BLOG POSTA composite organization in the commissioned study conducted by Forrester Consulting on behalf of Dataiku saw the following benefits:
reduction in time spent on data analysis, extraction, and preparation.
reduction in time spent on model lifecycle activities (training, deployment, and monitoring).
return on investment
net present value over three years.