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Introduction to streaming analytics with IBM Streams

About this series

These six videos will show you what IBM Streams is, what it can be used for, and how it differs from traditional batch processing systems like Spark and Hadoop.

Introduction to streaming analytics with IBM Streams

This video summarizes features and provides a general introduction to the streams runtime so that any developer who is curious about it can get a better understanding of what it is and how to use it.


Get started using IBM Watson studio streams flows

This video is an overview of streams flows and shows how to get started with IBM Watson Studio.


Real-time forecasting using R and IBM Watson Studio streams flows

The quickest way to get started with streaming analytics is with IBM Watson Studio Streams flows. This video is an overview of streams flows and shows how to get started with IBM Watson Studio. After training a model on static historical data, you can use it on real time data by integrating it with Watson Studio streams flows.


Create your first streams flow

Follow the steps in this video to create a simple streams flow. This video shows how to create a flow from scratch using the streams flow Canvas. It also shows how to ingest streaming data, filter it based on a condition, and then send it to Cloud Object Storage.


Use Python to process streaming data in Watson Studio streams flows

This video shows how to use the Python operator to add custom logic to streams flows. The application will process electricity usage data from smart meters to keep track of usage costs and contact high-usage customers via e-mail.


Ingest streaming data from IoT devices using Watson Studio streams flows

This video shows how you can use the drag-and-drop tooling in streams flows to create an application that ingests data from IoT devices.


Next steps

You can find more tutorials for streams flows here or view the full streams flows roadmap.

IBM Developer Staff