Streaming analytics basics for Python developers

Streaming analytics basics for Python developers

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Imagine you work for the IT department in a hospital and want to tap the life-saving potential of continuous data coming in from patients’ vital sign monitors. A Streams application, processing such data in real time, could make swift detections of dangerous anomalies of vital signs, and alert hospital staff when a patient needs immediate care. IBM® Streams® is an advanced stream processing platform that can ingest, filter, analyze, and correlate massive volumes of continuous data streams. Viewing and analyzing this data helps you make decisions while events are happening. Development in Streams has traditionally been done by using the Streams Processing Language (SPL). However, with the introduction of the Python Application API, developers like you can create streaming applications by using the Python language without first having to learn SPL. This course introduces you to the IBM Streams Python Application API.
Get started Essential Streams concepts Lab 1: create a simple Python application Lab 2: handle a variety of patient data Lab 3: anonymize and average data Lab 4: visualize data in a Python notebook Wrap up

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