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Apache Kafka and Apache Flink: An open-source match made in heaven

IBM Journey to AI blog

It allows your business to ingest continuous data streams as they happen and bring them to the forefront for analysis, enabling you to keep up with constant changes. Apache Kafka boasts many strong capabilities, such as delivering a high throughput and maintaining a high fault tolerance in the case of application failure.

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How Thomson Reuters delivers personalized content subscription plans at scale using Amazon Personalize

AWS Machine Learning Blog

The rules in this engine were predefined and written in SQL, which aside from posing a challenge to manage, also struggled to cope with the proliferation of data from TR’s various integrated data source. TR customer data is changing at a faster rate than the business rules can evolve to reflect changing customer needs.

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Comparing Tools For Data Processing Pipelines

The MLOps Blog

Data Processing : You need to save the processed data through computations such as aggregation, filtering and sorting. Data Storage : To store this processed data to retrieve it over time – be it a data warehouse or a data lake. Uses secure protocols for data security.