Data Wrangling: The Challenging Yourney from the Wild to the Lake

By Ignacio G. Terrizzano, P. Schwarz, M. Roth, John E. Colino. 2015

205 citations recorded by the source corpus.

How researchers see this paper

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A Survey on Data Collection for Machine Learning: A Big Data - AI Integration Perspective (2018, methodology): “Data discovery is necessary when one wants to share or search for new datasets and has become important as more datasets are available on the Web and corporate data lakes [19], [75].”
Goods: Organizing Google's Datasets (2016, result): “This approach is similar in spirit to the concept of data lakes [4, 22], where the lake comprises and continuously accumulates all the datasets generated within the enterprise.”
Managing Google's data lake: an overview of the Goods system (2016, background): “The ﬂip side of this explosion is the creation of a so called data lake [1, 2, 6]: a growing volume of internal datasets, with little codiﬁed information about their purpose, value, or origin.”
Navigating the Data Lake with DATAMARAN: Automatically Extracting Structure from Log Datasets (2017, background): “is phenomenon of accumulation of log datasets within enterprises has recently been referred to as the “data lake” problem [23, 45, 46].”