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Data / ML

Turbocharging Analytics at Uber with our Data Science Workbench

31 October 2017 / Global
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Figure 1: As depicted above, users of Uber’s data science workbench instantiate sessions in a web browser. All files/metadata created in an individual session are maintained by DSW’s management service, and sessions are back by Docker containers, which connect to Uber’s various data stores and libraries for batch analytics, real-time queries, and machine learning applications.
Figure 2: DSW’s Session Management Page lets users spin up RStudio and Jupyter sessions with the click of a button. The right-hand panel shows performance metrics associated with each session.
Figure 3: The right-hand panel on DSW’s File Browser lets users add comments and tags to individual files.
Figure 4: DSW’s Job Scheduler lets users schedule jobs on individual sessions, configure email notifications, and toggle which jobs are enabled.
Figure 5: Users can create Shiny Apps and view apps created by others from DSW’s Dashboards tab.
Figure 6: Since the toolbox’s March 2017 launch, users across the company have adopted DSW to empower data-driven decision-making.
Nikhil Joshi

Nikhil Joshi

Nikhil Joshi is a group product manager on Uber's Data Platform team.

Isabel Geracioti

Isabel Geracioti

Isabel Geracioti is a former Software Engineer on the Metadata Platform team under Data Platform at Uber. She worked on metadata-based projects including data quality and lineage.

Posted by Nikhil Joshi, Isabel Geracioti

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