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.
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