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HOUDAL : A Data Lake Implemented for Public Housing

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Résumé

Like all areas of economic activity, public housing is impacted by the rise of big data. While Business Intelligence and Data Science analyses are more or less mastered by social landlords, combining them inside a shared environment is still a challenge. Moreover, processing big data, such as geographical open data that sometimes exceed the capacity of traditional tools, raises a second issue. To face these problems, we propose to use a data lake, a system in which data of any type can be stored and from which various analyses can be performed. In this paper, we present a real use case on public housing that fueled our motivation to introduce a data lake. We also propose a data lake framework that is versatile enough to meet the challenges induced by the use case. Finally, we present HOUDAL, an implementation of a data lake based on our framework, which is operational and used by a social landlord.
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Dates et versions

hal-03573726 , version 1 (14-02-2022)

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Etienne Scholly, Cécile Favre, Eric Ferey, Sabine Loudcher. HOUDAL : A Data Lake Implemented for Public Housing. International Conference on Enterprise Information Systems, 2021, Online streaming, France. ⟨10.5220/0010418200390050⟩. ⟨hal-03573726⟩
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