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IoT Data Transformation

The programme is available as self-paced on-demand or as a live online classroom delivery.

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Course Overview

This course gives you the opportunity to explore the role of data analytics in IoT and find out what are the key steps to maximising the value of data generated from IoT devices. The expert course instructor will take you through the fundamental steps required to turn your organisation’s IoT data into valuable information for the business.

Key questions should be answered by any organisation that is embracing and offering IoT solutions and products, prior to embarking into IoT data analytics projects, to ensure success and avoid common pain-points. What do you expert out of your IoT data? What does the data even represent? Does your organisation have a strategy? The course will provide a structured approach to truly transform your IoT data into actionable business information and create a long-term and future-proof IoT data strategy.

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Live online or on-demand :

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Why choose this course?

Learning Outcomes

Key learning outcomes for the attendee

  • Learn how to unlock the business potential of IoT data
  • Understand and overcome some of the early IoT data analytics challenges
  • Discussing how IoT data can be transformed into useful business management information
  • Implement an IoT data strategy across the organisation
  • Identify possible roadblocks on your path towards creating value from IoT data

Benefits for the organisation

  • The course offers a structured approach to exploiting the analytics potential of IoT data within an organisation
  • Due to the size of the data sets generated by these devices, this course will help reduce the time it takes to realise its full analytics potential and streamline the process
  • Upskill teams to transform IoT data into meaningful information for the business
  • Teams will have the ability to build an IoT data strategy embracing analytics and visualisation tools

Programme Modules

Module 1

Understanding your data

  • What does the data represent?
  • What is it for?
  • Real world events vs system process monitoring

Module 2

Creating an IoT data strategy

  • What needs to be monitored?
  • Data collection frequency
  • New vs Existing Data Sets
  • Reporting frequency
  • Data retention requirements

Module 3

Analytics Environment

  • Data collection
  • Potential On-device analytics
  • Frequency of Analytics (streaming vs periodic)

Module 4

Transforming Data into Insights

  • Baseline monitoring
  • Composite data structures (inference)
  • Structuring data for analytics
  • The role of machine learning in IOT analytics

Module 5

Visualising Data

  • Reporting types
  • Complexity issues in visualisation
  • Multiple interpretation problem in big data

Live Virtual Classroom

Why choose a Virtual Classroom programme: