IoT Analytics

Companies are collecting massive quantities of data today from sensors and connected devices—data ripe for value creation. Using IoT analytics, they can surface valuable information about their products and services, consumers, corporate assets, environmental conditions, and numerous other factors affecting their business and the world. By applying analytics to incoming streams of IoT data, organizations can obtain actionable data insights that can be used to improve their products and the customer experience, detect and mitigate operational risk, uncover and eliminate inefficiencies, and identify new revenue opportunities. With the right IoT analytics platform, or a data platform that enables them to easily aggregate, manage, and analyze the diverse data gathered from connected products and machines, firms can realize the true value of the Internet of Things.

How companies are using and benefitting from IoT analytics

IoT analytics is the application of data analytics to the streams of information coming into the organization from networks of consumer, enterprise, and industrial, internet-connected devices. In industries ranging from manufacturing and transport to healthcare and retail, firms are using IoT analytics to monitor the health and status of people, machines, products, and their assets in order to:

  • Get a real-time, holistic view of multiple systems
  • Observe the lifecycle of products and learn about customer behavior and preferences
  • Carry out predictive maintenance and proactive customer service
  • Minimize downtime and improve production efficiency and service delivery
  • Automate inventory management and optimize supply chains

The benefits of an effective IoT analytics initiative are many and include increased productivity and transparency across the organization, reduced maintenance and labor costs, improved resource utilization, and greater customer satisfaction and loyalty. By analyzing IoT data, firms can enable smarter, faster decision-making and a data-driven approach to planning and problem-solving.

Maximizing your IoT analytics ROI

For firms that want to gain the most value from their connected device data and maximize the ROI of their IoT analytics program, here are some best practices to follow:

  • Ensure the quality and accuracy of your data by automating the profiling, or cleaning, of data to eliminate errors
  • Decide where to analyze your data based on the type of data collected, the type of analysis to be done, and your existing analytics infrastructure
  • Leverage a data platform that allows you to associate your IoT data with all your other data in order to gain deeper data insight
  • Empower your employees to explore and make their own discoveries in IoT data using data discovery tools

What’s required for a successful IoT analytics strategy

The greatest challenge for firms struggling to leverage IoT analytics is making all the data accessible to and meaningful for their decision-makers and other stakeholders in the organization. Aggregating, managing, and storing diverse types of data from multiple sensors and sources can be difficult and time-consuming. Data integration is complicated when high volumes of data are streaming in from devices and systems that were not developed for compatibility.

A successful IoT analytics program requires the use of an appropriate data intelligence platform that provides data ingestion, stream processing, data transformation, data management, and data analytics tools. Firms need a data analytics platform that will enable them to:

  • Connect to and load data from their IoT platform(s) and other enterprise systems and blend and manage various data types
  • Deploy on-premises, in the cloud, or a hybrid environment depending on their needs and scale as their requirements change
  • Allow their employees to easily access and explore data and build their own dashboards and other analytics applications
  • Manage the governance of data while promoting sharing and collaboration of analytics across the organization

An end-to-end data management and analytics solution for IoT analytics

Qlik, the pioneer of user-driven business intelligence solutions, offers organizations an end-to-end real-time data integration and data analytics platform for IoT analytics. Companies in industries ranging from automotive manufacturing to energy and utilities are using Qlik to transform their sensor and connected device data into real value—to surface deeper insights from their IoT data, better serve their customers, boost productivity, drive innovation, and find new ways to monetize data. The flexibility of Qlik’s analytics platform allows firms to combine their sensor data with any number of internal and external data sources and provides them with advanced analytics capabilities to support complex use cases like predictive maintenance.

Out-of-the-box data connectors let users seamlessly combine data from smart devices, sensors, and clickstreams with data from production, CRM, and ERP systems as well as web and third-party data. With Qlik’s Associative Engine running in the background, users can quickly identify important relationships between machine-generated data and other information assets while built-in AI helps users of all skill levels combine, load, model, and manipulate data efficiently. Through an intuitive visual interface, even non-technical users can aggregate, visualize, and discover important patterns and trends in data streams.

A centralized analytics hub provides users with a way to easily share the insights they discover while also ensuring that the right people have access to the right data—providing proper data governance without lessening agility. Qlik’s highly flexible platform lets you connect to the IoT platform of your choice, deploy the way you want, and extend, customize, and embed IoT analytics with open APIs. Qlik is the most complete solution for modern analytics available on the market, supporting all BI and analytics use cases from self-service analytics and business intelligence reporting to conversational and mobile analytics.


What are some examples of IoT devices or applications?

They include wearable devices like smartwatches, various smart products for the home such as smart thermometers and connected appliances, and healthcare monitoring devices. Sensors are also being used in autonomous vehicles and farming equipment and for inventory tracking and management, quality control, and supply chain optimization.

What are the benefits of IoT analytics?

The benefits include greater visibility into customer behavior and business processes, increased employee productivity and customer engagement, reduced operational costs through automation and better resource utilization, improved planning and scheduling, and faster, smarter decision making.

What is the role of data analytics in IoT?

Data analytics is what allows organizations to extract meaningful information or actionable insights from their IoT data. It enables users to identify important patterns, trends, and anomalies in the data collected from connected devices. This information can be used to inform decision making, drive automation, support strategic planning, and more.


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