2019•Proceedings of the VLDB EndowmentRequires access

Data lake management

Fatemeh Nargesian, Erkang Zhu, Renée J. Miller, Ken Qian Pu, Patricia C. Arocena

Open publisher page 249 citations

Abstract

The ubiquity of data lakes has created fascinating new challenges for data management research. In this tutorial, we review the state-of-the-art in data management for data lakes. We consider how data lakes are introducing new problems including dataset discovery and how they are changing the requirements for classic problems including data extraction, data cleaning, data integration, data versioning, and metadata management.

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What this paper is about

The ubiquity of data lakes has created fascinating new challenges for data management research. In this tutorial, we review the state-of-the-art in data management for data lakes. We consider how data lakes are introducing new problems including dataset discovery and how they are changing the requirements for classic problems including data extraction, data cleaning, data integration, data versioning, and metadata management.

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OpenAlex reports 249 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The ubiquity of data lakes has created fascinating new challenges for data management research. In this tutorial, we review the state-of-the-art in data management for data lakes. We consider how data lakes are introducing new problems including dataset discovery and how they are changing the requirements for classic problems including data extraction, data cleaning, data integration, data versioning, and metadata management.

Key concepts: Metadata, Data management, Metadata management, Data science, Data management plan, Computer science, Data integration, Software versioning

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