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Databricks@Smartsheet

Smartsheet Extends Delta Lake Across Applied Machine Learning

Smartsheet, an information technology organization in the United States, uses Delta Lake from Databricks to support applied machine learning for data scientists and ML engineers.

Value results

CategoryValue result
ProductivityFewer stalled items because feature pipelines has a clear owner
ProductivityHandoffs in applied machine learning sit in a shared queue instead of a mailbox trail
Risk and complianceDelta Lake is the governed place data scientists and ML engineers use for applied machine learning

Story

Inside Smartsheet, applied machine learning used to depend on whoever still had the latest file. That pattern is common in information technology groups working out of the United States. Data scientists and ML engineers needed a system that would still make sense after the original project team moved on.

Smartsheet uses Delta Lake from Databricks as the working layer for feature pipelines. Databricks provides a lakehouse platform for data engineering, analytics, and AI, with Unity Catalog and Mosaic AI for governed models. The practical change is simple: applied machine learning has a home, and reviews happen there instead of in a forwarded thread.

Nothing in this writeup invents a savings number. What Smartsheet gets from Databricks is a durable place to run applied machine learning and a way for data scientists and ML engineers to see the same feature pipelines at the same time.

Relationship map

Smartsheet uses Databricks, Cartesia, Coupa, Unity, Cisco. Shared with AstraZeneca, Biogen, Grammarly, Hotels.com, Konica Minolta. Industry: Information Technology. Value: Productivity, Risk and compliance. Drag nodes, filter types, or expand a node to follow more commonalities.

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