Is your Data Warehouse serving as a collaborative platform for Data Science?

Organizations are increasingly realising they need to consolidate the data input, pipelines and outputs of their data science work into a central place for both governance and reuse. This session will cover how a Data Warehouse can be used for both feature engineering and as a shared feature-repository for Data Science teams.  We will show how capabilities of Snowflakes Data Warehouse service lend themselves to this use.

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Speaker Bio

Simon is the EMEA Field CTO at Snowflake where he helps organisations to maximise the value they can derive from their data assets and investment in Snowflake. He has worked with organisations across EMEA in the field of Big Data, Data Warehousing and Advanced Analytics for over 25 years, through the full data life-cycle from data integration, model and governance, storage and consumption. In his current role Simon works closely with customers, to ensure they are able to take full advantage of the unique platform which Snowflake provides. Working within the Snowflake Product team the role includes bringing new features and capabilities to Snowflake customers and providing direct feedback to developers and product management on their adoption and experiences.

September 26 @ 16:00
16:00 — 16:30 (30′)

Stage 1 | Data Strategy & Governance

Simon Field – Field CTO | Snowflake

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