Life and Death of Data in Data Lakes: Preserving Data Usability and Responsible Governance

Derakhshannia, Marzieh; Gervet, Carmen; Hajj-Hassan, Hicham; Laurent, Anne; Martin, Arnaud

doi:10.1007/978-3-030-34770-3_24

Cited by 2 publications

(1 citation statement)

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“…In addition, a key challenge lies in the evaluation of data usage during their lifespan, because a data lake stores data that may be retrieved or queried in the future, rather than serving an immediate need [25].…”

Section: Our Approach and Contributionmentioning

confidence: 99%

Data Lake Governance: Towards a Systemic and Natural Ecosystem Analogy

Derakhshannia

Gervet²,

Hajj-Hassan³

et al. 2020

Future Internet

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The realm of big data has brought new venues for knowledge acquisition, but also major challenges including data interoperability and effective management. The great volume of miscellaneous data renders the generation of new knowledge a complex data analysis process. Presently, big data technologies provide multiple solutions and tools towards the semantic analysis of heterogeneous data, including their accessibility and reusability. However, in addition to learning from data, we are faced with the issue of data storage and management in a cost-effective and reliable manner. This is the core topic of this paper. A data lake, inspired by the natural lake, is a centralized data repository that stores all kinds of data in any format and structure. This allows any type of data to be ingested into the data lake without any restriction or normalization. This could lead to a critical problem known as data swamp, which can contain invalid or incoherent data that adds no values for further knowledge acquisition. To deal with the potential avalanche of data, some legislation is required to turn such heterogeneous datasets into manageable data. In this article, we address this problem and propose some solutions concerning innovative methods, derived from a multidisciplinary science perspective to manage data lake. The proposed methods imitate the supply chain management and natural lake principles with an emphasis on the importance of the data life cycle, to implement responsible data governance for the data lake.

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Section: Our Approach and Contributionmentioning

confidence: 99%