Customer 360 – Part 2 – Data Ingestion

Building a Customer 360 solution on Couchbase involves a complex process of extracting, transforming, and loading (ETL) data from various source systems such as CRM, ERP, and even mainframes into Couchbase. The author emphasizes the importance of simplicity in this process, suggesting using Kafka streams to transfer data in JSON format directly into Couchbase, despite the inherent challenges of integrating disjointed data models from different systems. The solution includes using Couchbase's Eventing system to update and combine data in real time, creating a cohesive customer data model. Although Couchbase advocates for analytics without ETL, in this case, an ETL process is necessary, albeit potentially in a real-time context, depending on the data extraction schedule. The author argues that using Couchbase, in conjunction with existing infrastructure like Kafka, offers a simpler and more integrated approach than relying on multiple external ETL tools and systems, allowing for better performance and ease of use.

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