Amalur: Next-generation Data Integration in Data Lakes

Research output: Contribution to conferenceAbstractScientific

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Abstract

Data science workflows often require extracting, preparing and integrating data from multiple data sources. This is a cumbersome and slow process: most of the times, data scientists prepare data in a data processing system or a data lake, and export it as a table, in order for it to be consumed by a Machine Learning (ML) algorithm. Recent advances in the area of factorized ML, allow us to push down certain linear algebra (LA) operators, executing them closer to the data sources. With this work, we revisit classic data integration (DI) systems and see how these fit into modern data lakes that are meant to support LA as a first-class citizen.

Original languageEnglish
Number of pages1
Publication statusPublished - 2022
Event12th Annual Conference on Innovative Data Systems Research, CIDR 2022 - Santa Cruz, United States
Duration: 9 Jan 202212 Jan 2022

Conference

Conference12th Annual Conference on Innovative Data Systems Research, CIDR 2022
Country/TerritoryUnited States
CitySanta Cruz
Period9/01/2212/01/22

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