Decentralized Data Mesh With Apache Kafka in Financial Services

Digital transformation requires agility and fast time to market as critical factors for success in any enterprise. The decentralization with a data mesh separates applications and business units into independent domains. Data sharing in real-time with data streaming helps provide information in the proper context to the correct application at the right time. This article explores a case study from the financial services sector where a data mesh was built across countries for loosely coupled data sharing but standardized enterprise-wide data governance.

Data Mesh: The Need for Real-Time Data Streaming

If there were a buzzword of the hour, it would undoubtedly be “data mesh!” This new architectural paradigm unlocks analytic and transactional data at scale and enables rapid access to an ever-growing number of distributed domain datasets for various usage scenarios. The data mesh addresses the most common weaknesses of the traditional centralized data lake or data platform architecture. The heart of a decentralized data mesh infrastructure must be real-time, reliable, and scalable:

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