Streamlining Data Science with Snowflake

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Snowflake For Data Science

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Presentation Description:

Data science and machine learning (ML) are revolutionizing how organizations make business and product decisions, and how they retain and attract new customers.
But data science isn’t easy. It requires fast access to all of an organization’s data, powerful data engineering capabilities, and support for an ever-expanding ecosystem of ML tools, frameworks, and libraries.
In this session, Snowflake product leaders will demonstrate how Snowflake streamlines the data science process by:

Managing all types of data for ML
Enabling data pipelines with custom code beyond SQL
Operationalizing ML
Orchestrating data science resources outside of Snowflake
Integrating directly with data science partners
(external functions, Java UDF, Unstructured data management)

Presentation Track: Supercharge Your Analytics and Data Science
Presentation Date: November 29, 2020
Presentation Speaker(s): Ahmad Khan
Frank’s Comment: Okay. I’m going to try and make this one. Again, I’m biased because I have worked with Ahmad on a few engagements and he knows his stuff. He usually has great presentations and while Snowflake needs a lot of work to do in order to take on Data Science wor

Overview ITS:

In this session, we learn exactly how data science is transforming businesses by revolutionizing how organizations make business and product decisions, and how they retain and attract new customers. Data science, however, isn’t easy, which is why Snowflake streamlines the data science process, easily overcoming the challenges of siloed diverse data, slow complex environments, and locked machine learning ecosystems.
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