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Crosser Cleaning Data Reduction Flow Illustrations

A common IoT scenario is collecting data from various sensors and devices. Often communicating with different protocols and setups. To be able to use that data, the user must normalize and prepare the data for further processing.

This is a simple example of such scenario built in Crosser Flow Studio:

  1. Collect data from heterogeneous sources
  2. Remove invalid data
  3. Select relevant data
  4. Normalize data structures
  5. Add metadata
  6. Anonymize the data
  7. Filter and/or aggregate to reduce the amount of data, or to hide sensitive internal details

Introduction to Cleaning & Normalization of IOT Data

Free on-demand webinar

Learn more about Cleaning and Normalization of IoT Data at the Edge. During this 30 min session, Crosser CTO Goran Appelquist, will introduce you to designing a functional IoT data flow for industrial usage with the Crosser Flow Studio visual design tool.

Level: Intermediate
Time: 00:36:19

Start Innovating Today

Try Crosser for Free

Sign up for a free trial account. Design and deploy your first Flows today.

  1. Sign up
  2. Login and start designing your data flows
  3. Run the flow in Crosser test environment or download local test node
  4. Test with real data

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