Analytic Solutions

Analytic Solutions

Internet of Things (IoT) analytics enables organizations to leverage the massive amounts of data generated by IoT devices, using analytics stacks. IoT analytics is often considered a subset of big data, involved with combining heterogeneous streams and transforming them into consistent and accurate insights.

• Increased visibility and control, leading to faster decision making
• Faster problem solving and prevention of recurring problems
• Reduced operational costs through automation and smarter utilization of resources
• More accurate attribution of problems, leading to better solutions – faster

Insights generated by IoT streams can help organizations improve many aspects of their operations. However, it is often complex to integrate the many types of IoT devices with existing ecosystems and analytics tools. This is why, insofar, organizations deployed Industrial IoT (IIoT), a technology built for collecting and analysing data from sensors. When sensors are placed on key manufacturing equipment, weather stations, delivery trucks, pipelines, and smart meters, organizations can properly integrate devices with analysis tooling. IoT data analytics can help other industries, like healthcare facilities and data centres, better leverage their data.

IoT analytics automates the most difficult tasks associated with analysis of the IoT data and is a fully managed service which makes it easy to run complicated data analytics algorithms. IoT analytics platform to run analytics on the edge and get accurate insights. With IoT Analytics, we can store only the relevant data from the sensor and enrich the data with device specific metadata such as device type and locations. IoT Data Analytics is a fully managed and can support up to petabytes of IoT data. So, you can easily manage your IoT applications, without worrying about the hardware and infrastructure. Using IoT Analytics users can, easily run queries on IoT data, run time analytics, optimize data storage and analyse using machine learning analytics.

Instead of collecting and trying to use all data, sophisticated IoT analytics tools know how to collect the most significant data points, perform quick analysis, and provide insights relevant to the products and services. IoT analytics can save valuable time, reducing tasks related to the integration of data sources. The result is a data analytics pipeline that provides access to data. Ideally, any role in the organization can use the workflow to ask questions and gain insights.