GitHub / AbdullahMu / Data-Streaming-Nanodegree-Project_02-Evaluate-Human-Balance-with-Spark-Streaming

Design data streaming architecture and API for a real-life application called the Step Trending Electronic Data Interface (STEDI). It is a working application used to assess fall risk for seniors. When a senior takes a test, they are scored using an index which reflects the likelihood of falling, and potentially sustaining an injury in the course of walking. STEDI uses a Redis datastore for risk score and other data. The Data Science team has completed a working graph for population risk at a STEDI clinic. The problem is the data is not populated yet. You will work with Kafka Connect Redis Source events and Business Events to create a Kafka topic containing anonymized risk scores of seniors in the clinic.

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Topics: apache-kafka, apache-spark, api, base64, data-streaming, kafka, redis, spark-streaming, spark-streaming-kafka

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