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Anomaly detection in streaming time series data with online learning using Amazon Managed Service for Apache Flink

AWS Machine Learning Blog

It initially sources input time series data from Amazon Managed Streaming for Apache Kafka (Amazon MSK) using this live stream for model training. Post-training, the model continues to process incoming data points from the stream. It evaluates these points against the historical trends of the corresponding time series.

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How data engineers tame Big Data?

Dataconomy

They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. This involves working closely with data analysts and data scientists to ensure that data is stored, processed, and analyzed efficiently to derive insights that inform decision-making.

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

AWS Machine Learning Blog

A DataBrew job extracts the data from the TR data warehouse for the users who are eligible to provide recommendations during renewal based on the current subscription plan and recent activity. Then the events are ingested into TR’s centralized streaming platform, which is built on top of Amazon Managed Streaming for Kafka (Amazon MSK).

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Top 15 Data Analytics Projects in 2023 for beginners to Experienced

Pickl AI

Real-time Data Stream Analysis: Use Python with libraries like Apache Kafka and Apache Spark to process and analyze real-time data streams from sources like Twitter, sensors, or website logs. Implement real-time analytics to monitor trends or anomalies in the data.

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Predicting the Future of Data Science

Pickl AI

Furthermore, the demand for skilled data professionals continues to rise; searches for “data analyst” roles have doubled in recent years as companies seek to harness the power of their data. Apache Kafka), organisations can now analyse vast amounts of data as it is generated.