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Taking data-driven decisions with the analytics of things

The Internet of Things generates massive amounts of structured and unstructured data, requiring a new class of big data analytics to uncover and capture value.

These few words – included inside the Analytics Trends 2015 report recently produced by Deloitte – perfectly introduce the topic of Analytics of Things (AoT).

Every device connected to a network automatically transfers data. Sensors generate a huge amount of data, that becomes useful just if processed and turned into predictions (or other valuable information manageable and actually “consumed” by users).

Analytics can be described as turning data into information.

Analytics can be Descriptive (What happened and why?), Predictive (What is (probably) going to happen?) or Prescriptive (What should I do about it?). These distinctions are still valuable for the Analytics of Thingsthe guide to IoT Analytics written by Tellient underlines a completely new business arena where companies start competing on (big) data.

Wal-Mart is now both a retailer and a data company, creating a “social genome” to integrate big data analysis of their customers’ social data and purchasing habits. They call it that because it is essentially a “living organism” that drives their business.

Data is where opportunities are for disruption: who is going to own and smartly manage them? New opportunities disclosed by IoT are (still) to be discovered, and Analytics of Things may open interesting scenarios also for the Motorsport world. Now, it’s up to you: any other disruptive ideas about how Internet of Things could be re-imagined and exploited in the automotive industry and racing?

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