Integrating Data Lakes and Data Warehouses for Scalable Enterprise Analytics

Abstract

This study explores the integration of data lakes and data warehouses as a unified analytics architecture for scalable enterprise analytics, highlighting how the combination of flexible, schema-on-read storage with structured, high-performance querying enables organizations to handle large volumes of heterogeneous data, improve data accessibility, support advanced analytics and machine learning, and achieve cost-efficient, real-time, and batch-driven decision-making across the enterprise.