International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Volume 7 Issue 4
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Secure Data Lake Architectures for Public Sector Analytics

Author(s) Anusha Joodala
Country United States
Abstract The proliferation of big data technologies, particularly data lakes, in the public sector has allowed for better management and analysis of large and heterogenous data sets ranging from structured to unstructured data. Data lakes enable raw data to be stored in a flexible way, which can then be used to make a data analysis and decision, for example, in several public areas, including healthcare, transportation, and law enforcement. But with this growth in both volume and sensitivity of data, the challenges of keeping sensitive information secure in line with increased regulation, while demonstrating transparency around data use, also become even more complex. In this paper, we analyze secure data lake architectures for the public sector, with a strong focus on implementing strong security measures such as encryption, and access controls and compliance considerations. It considers the security risks posed to public institutions and presents a series of best practices for safeguarding data integrity, confidentiality and privacy. The findings highlight the importance of a full security spectrum which balances accessibility and protection, meaning data lakes can be harnessed effectively for public sector analytics in a way that keeps citizen information safe and organizations’ integrity intact.
Keywords Data lakes, Public sector, Data security, Compliance, Analytics.
Field Engineering
Published In Volume 7, Issue 4, July-August 2025
Published On 2025-07-22
DOI https://doi.org/10.36948/ijfmr.2025.v07i04.50896
Short DOI https://doi.org/g9tx9s
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E-ISSN 2582-2160
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