Journal of Data Analysis and Information Processing

Volume 13, Issue 4 (November 2025)

ISSN Print: 2327-7211   ISSN Online: 2327-7203

Google-based Impact Factor: 3.58  Citations  

Data Lakes as a Centralized Integration Layer in Enterprise Environments: Approaches and Benefits for Scalability and Performance

  XML Download Download as PDF (Size: 3038KB)  PP. 467-486  
DOI: 10.4236/jdaip.2025.134027    74 Downloads   388 Views  

ABSTRACT

Enterprise application integration encounters substantial hurdles, particularly in intricate contexts that require elevated scalability and speed. Transactional applications directly accessed by many systems frequently overload databases, undermining process efficiency. This paper examines the utilization of data lakes—historically used for data analysis—as a centralized integration layer that accommodates various temporalities and consumption modalities. The suggested method diminishes system interdependence and the burden on transactional databases, enhancing scalability and data governance in both monolithic and distributed frameworks.

Share and Cite:

Cavalcanti Pereira, C. D. (2025) Data Lakes as a Centralized Integration Layer in Enterprise Environments: Approaches and Benefits for Scalability and Performance. Journal of Data Analysis and Information Processing, 13, 467-486. doi: 10.4236/jdaip.2025.134027.

Cited by

No relevant information.

Copyright © 2026 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.