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Part I: Foundations of Real-Time Data Ecosystems Section 1: The Paradigm Shift from Batch to Real-Time Processing The digital transformation of modern enterprises is predicated on the ability to harness Read More …
Executive Summary The contemporary data landscape is defined by a fundamental shift from periodic, high-latency batch processing to continuous, real-time stream processing. This paradigm evolution is driven by the business Read More …
Introduction In today’s data-driven world, businesses and organizations need to process and analyze vast amounts of data in real time. Kafka, a distributed event streaming platform, has emerged as a Read More …