Data Wrangling with Apache Kafka and KSQL

The great thing about Kafka is its ability to build systems in which functionality is compartmentalized. Ingest is handled by one process (in this case, Kafka Connect), and transformation is handled by a series of KSQL statements. Each can be modified and switched out for another without impacting the pipeline we’re building. Keeping them separate makes it easier to perform important activities such as testing, troubleshooting and analyzing performance metrics. It also means that we can extend data pipelines easily.
We may have a single use case in mind when initially building it, and one way to do this would be building a single application that pulls data from REST endpoints before cleansing, wrangling and writing it out to the original target. But now if we want to add other targets, we have to modify that application, which becomes more complex and risky. Instead, by breaking up the processes and

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