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IoT analytics is the use of data analysis techniques and tools to extract useful information from the massive data volumes produced by connected Internet of Things devices.
IoT analytics is an application of data analytics to analyze the information streams that networks of consumer, business, and industrial internet-connected devices. Businesses are utilizing IoT analytics to track the health and status of people, machines, products, and other assets in a variety of sectors, including industries ranging from manufacturing and transportation to healthcare and retail.
There are numerous benefits of an effective IoT analytics initiative that include higher operational efficiency, better resource utilization, lower maintenance and labor costs, and greater customer satisfaction and loyalty. Businesses may enable smarter, quicker decision-making as well as a data-driven approach to planning and problem-solving by evaluating IoT data.
Below listed are some recommended practices for businesses looking to make the most out of their connected device data and increase the ROI of their IoT analytics program:
Making all the data available and useful for the organization's decision-makers and other stakeholders is the biggest challenge faced by businesses trying to use IoT analytics. It can be tedious for businesses to collect, manage, and store different types of data from various sensors and sources. Data integration becomes complex when massive data volumes flow in from different devices and systems that weren’t designed for compatibility.
A suitable data intelligence platform that offers tools for data ingestion, stream processing, data analytics, data transformation, and data management is necessary for a successful IoT analytics program. Businesses seek a data analytics platform that enables them to:
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