IoT Analytics
Realize actionable insights from IoT data with IoT analytics
What is IoT analytics?
IoT analytics is the analysis of data generated from connected devices. The true value of IoT solutions lies in the data. Every connected device can generate thousands—or even millions—of data points every day. Contained in that IoT data are the answers to business problems, diagnoses for machine failures, and even predictions for the future. The analytics process can be simplified into three steps: first, capture and process data; next, apply logic to the data to unlock value; and finally, produce insights to enhance decision-making and operations across the enterprise.
How does IoT analytics work? Make your IoT data work for you
IoT analytics is central to digital transformation. High-speed IoT data acquisition is combined with simplified access to required contextual information along with artificial intelligence and machine learning capabilities. The insights derived from this powerful combination provide unprecedented opportunities to improve decision-making, processes, and operational outcomes both across the enterprise and for customers.
Consider these four categories of IoT analytics:
- Descriptive analytics to understand the current situation
- Diagnostic analytics to understand why the current situation is happening
- Predictive analytics to understand when a negative event may occur before it does
- Prescriptive analytics to suggest the next best action based on a given event or condition
Unlocking IoT value through analytics
A sound IoT innovation strategy must begin with an understanding of the role analytics will play. Learn how analytics can unlock the value of your IoT investment and provide you with insights that are key to gaining a powerful competitive advantage.
IoT analytics use cases and applications
Smart Factories
Manufacturers equip their assets and production lines with sensors to monitor performance. This allows them to monitor the quantity and quality of the assets they are producing. Better quality products lead to reduced costs and scrap along with better customer experiences—all of which contribute to revenue gains.
Connected Products
In addition to being able to leverage IoT data to improve factory processes, manufacturers can use IoT analytics to understand how the things they have built are performing in the real world.
New Business Models
Vendors that used to simply sell products are now able to sell those products as a service, where customers pay based on monthly usage. Manufacturers are also able to offer other value-added services such as over-the-air updates to software.
IoT data case studies
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