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The Need for Tabular Representation Learning: An Industry Perspective
Joyce Cahoon · Alexandra Savelieva · Andreas Mueller · Avrilia Floratou · Carlo Curino · Hiren Patel · Jordan Henkel · Markus Weimer · Roman Batoukov · Shaleen Deep · Venkatesh Emani · Richard Wydrowski · Nellie Gustafsson

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in Table Representation Learning »
Event URL: https://openreview.net/forum?id=jk4B84qmlXJ »
The total addressable market for data and intelligence applications has been estimated at \$70B. This includes the \$11B market for data integration, which is estimated to grow at 25\% in the coming year; \$35B market for analytics, growing at 11\%; and \$19B market for business intelligence, growing at 8\%. Given this data-driven future and the scale at which Microsoft operates (serving over 300K organizations with 50M+ end users), we leverage telemetry across our external and internal cloud and platform services (e.g., Azure, Microsoft 365, Visual Studio, etc.) to gain an understanding of our customer workloads and their constraints at play.
Keywords: Table Representation Learning

Author Information

Joyce Cahoon (Microsoft)

I am a Data & Applied Scientist in Microsoft’s Gray Systems Lab working to develop and integrate machine learning methods that improve the efficiency of data-intensive systems. I am also involved in efforts to democratize data science, by contributing towards the development of tools that make interacting and visualizing data, and building models with data, more accessible to the public. Prior to joining Microsoft, I completed my Ph.D. in Statistics from North Carolina State University in 2020 and my B.Sc. in Biomedical Engineering and Economics from Duke University in 2013.

Alexandra Savelieva
Andreas Mueller (Columbia University)
Avrilia Floratou
Carlo Curino (Microsoft)
Hiren Patel
Jordan Henkel
Markus Weimer (Microsoft)
Roman Batoukov
Shaleen Deep (University of Wisconsin, Madison)
Venkatesh Emani
Richard Wydrowski
Nellie Gustafsson

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