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MINOR: Fix typo in docs (#7158)
Reviewer: Matthias J. Sax <matthias@confluent.io>
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@ -60,7 +60,7 @@ and much lower end-to-end latency.
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Many users of Kafka process data in processing pipelines consisting of multiple stages, where raw input data is consumed from Kafka topics and then
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aggregated, enriched, or otherwise transformed into new topics for further consumption or follow-up processing.
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For example, a processing pipeline for recommending news articles might crawl article content from RSS feeds and publish it to an "articles" topic;
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further processing might normalize or deduplicate this content and published the cleansed article content to a new topic;
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further processing might normalize or deduplicate this content and publish the cleansed article content to a new topic;
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a final processing stage might attempt to recommend this content to users.
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Such processing pipelines create graphs of real-time data flows based on the individual topics.
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Starting in 0.10.0.0, a light-weight but powerful stream processing library called <a href="/documentation/streams">Kafka Streams</a>
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