Leveraging the Data Lake: Current State and Challenges
Leveraging the Data Lake: Current State and Challenges
复制标题
利用数据湖：现状和挑战
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
B. Mitschang
中科院分区：
文献类型：
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作者：
Corinna Giebler;Christoph Gröger;Eva Hoos;H. Schwarz;B. Mitschang
数字化转型导致大量异构数据挑战企业中的传统数据仓库解决方案。为了利用这些复杂的数据获得竞争优势，数据湖最近成为一个更灵活、更强大的数据分析概念。然而，现有的文献数据湖是相当模糊和不完整的，已经提出的各种实现方法既不涵盖数据湖的所有方面，也没有提供一个全面的设计和实现策略。因此，企业在构建数据湖时面临着多重挑战。为了解决这些缺点，我们调查了现有的数据湖文献，并讨论了数据湖的各种设计和实现方面，例如治理或数据模型。基于这些见解，我们确定了有关（1）数据湖架构、（2）数据湖治理和（3）实现数据湖的全面战略的挑战和研究差距。这些挑战仍然需要解决，以成功地在实践中利用数据湖。
The digital transformation leads to massive amounts of heterogeneous data challenging traditional data warehouse solutions in enterprises. In order to exploit these complex data for competitive advantages, the data lake recently emerged as a concept for more flexible and powerful data analytics. However, existing literature on data lakes is rather vague and incomplete, and the various realization approaches that have been proposed neither cover all aspects of data lakes nor do they provide a comprehensive design and realization strategy. Hence, enterprises face multiple challenges when building data lakes. To address these shortcomings, we investigate existing data lake literature and discuss various design and realization aspects for data lakes, such as governance or data models. Based on these insights, we identify challenges and research gaps concerning (1) data lake architecture, (2) data lake governance, and (3) a comprehensive strategy to realize data lakes. These challenges still need to be addressed to successfully leverage the data lake in practice.