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What is IoT Analytics? What's Required for a Successful IoT Analytics Strategy?

Internet of Things (IoT) Analytics refers to the use of data analysis tools and techniques to extract value from massive data volumes generated by connected IoT devices.

Meaning of IoT Analytics

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.

How is IoT Analytics useful and beneficial for businesses?

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.

  • Get access to a comprehensive, real-time perspective of several systems.
  • Study consumer behavior and preferences by keeping an eye on the lifecycle of items.
  • Perform proactive customer service and preventative maintenance.
  • Reduce downtime, boost production effectiveness, and enhance service delivery.
  • Streamline supply chains and automate inventory management.

  • 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.

    Maximizing your IoT Analytics ROI

    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:

  • By automating data profiling & cleaning, to eradicate errors, you can ensure data quality and accuracy.
  • Based on the types of data collected, the types of analyses to be performed, and your existing analytics infrastructure, choose where to conduct data analysis.
  • Utilize a data platform that enables you to connect your IoT data to all of your other data in order to acquire actionable data insights.
  • Give your staff access to data discovery tools so they may explore more about IoT data things.

  • What’s required for a successful IoT Analytics Strategy?

    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:

  • Connect to their IoT platform(s), and other enterprise systems, and load data from those, as well as merge and manage multiple data kinds.
  • Deploy in the cloud, on-premises, or in a hybrid environment based on their needs and scale as requirements change.
  • Make data easily accessible to your staff so they can study it, create their own dashboards, and use other analytics tools.
  • Manage data governance while encouraging analytics sharing and cooperation within the enterprise.

  • READ MORE: Building Smart Factories With IoT And Analytics 3 Best Examples Of IIoT In Action

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