Data lakes: Opportunities, Challenges, Threats and Ways to Mitigate Them

Abstract

Data lakes, which collect and store huge amounts of structured and unstructured data, are currently one of the most important technological tools. Their structure differs from traditional databases, as they are more flexible and allow organizations to store diverse data in a single repository for further processing and analysis. Their use is advisable in many fields, ranging from business and science to public administration. However, the rapid development of data lakes presents new challenges. The paper presents the key characteristics of data lakes and data warehouses, along with a comparative analysis. It discusses the opportunities for using data lakes, which are related to the diversity of the data stored within them. The main stages of data mining from lakes are presented. The strengths of using data lakes are also described. The paper places great emphasis on analyzing the risks associated with data lakes and proposes ways to mitigate them and the future prospects of data lakes are presented. The paper places significant emphasis on analyzing the risks associated with data lakes and proposes ways to mitigate them. Future perspectives for data lakes are also presented. Working with data lakes is a complex but important process. With the right approach and consideration of the challenges outlined in this paper, organizations will be able to maximize the potential of data lakes and gain competitive advantages.

References

Badri Meparishvili, Guram Tsertsvadze, Gulnara Janelidze Big Data Analitics, Tbilisi, GTU 2020, ISBN 244pp
Philip Russom, Data Lakes, © 2017 by TDWI, a division of 1105 Media, Inc., 40pp
Ben Sharma, Architecting Data Lakes, USA 2018, 50pp
Rihan Hai Christoph Quix Matthias Jark, Data lake concept and systems:17jun, 2021
Tomcy John, Pankaj Misra, Data Lake for Enterprises: Lambda Architecture for building enterprise data systems, 31 may, 2017
Corinna Giebler, Christoph Gröger, Eva Hoos, Rebecca Eichler, Holger Schwarz, Bernhard Mitschang, The Data Lake Architecture Framework: A Foundation for Building a Comprehensive Data Lake Architecture, Conference Paper· March 2021 DOI: 10.18420/btw2021-19z