Introduction
IoT solutions find their use-cases across various industries – Logistics, warehouse monitoring, manufacturing, quality management, facility management, vehicles in transit and more.
The volume of IoT sensor data is growing each day and the need to analyze and gather insights from them is also growing at a rapid pace.
As an organisation, one needs a robust IoT Analytics solution to analyze the historical data as well as real time data. With the introduction of Artificial Intelligence (AI) and machine learning (ML) technologies, advance IoT analytics solutions are also capable of predicting the occurrence of a future event (e.g: Predictive maintenance of industrial machinery).
For your IoT data analytics needs, you can either go with custom IoT analytic solutions or choose from the top IoT analytic solutions available in the market to integrate it with your existing IoT applications.
Let’s look at few of the top (IDC report) IoT data analytics tools in the market.
Microsoft Azure Stream Analytics
Microsoft’s Azure Stream Analytics can be easily integrated with Azure IoT hub and Azure IoT suite to perform real time analytics on the IoT sensor data.  Azure Stream Analytics helps companies deploy AI powered real time analytics and unlock the full value from the data. It’s also easy to create dashboards with Power BI and visualize the data and to see actionable insights.
AWS IoT Analytics
AWS 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. Â It is one of the easiest IoT analytics platform to run analytics on the edge and get accurate insights. With AWS 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.
AWS 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 AWS IoT Analytics users can, easily run queries on IoT data, run time analytics, optimize data storage and analyze using machine learning. AWS has a pay as you go pricing plan which enables companies of all sizes to test and choose AWS IoT analytics.
SAP Analytics Cloud
SAP Analytics Cloud has options to integrate IoT data to its analytics solution and analyze and visualize the data better. SAP Analytics cloud is enhanced with the power of predictive analytics and machine learning technology. SAP also has Streaming Lite module, which is a to-the-edge component designed to remotely deploy streaming projects. Â Streaming Lite is relevant if you wish to deploy projects on remote gateway devices – it is not required as part of a standard smart data streaming installation.
IBM Watson IoT Platform
Analytics is a part of IBM Watson’s IoT platform. With this solution users can easily analyze and visualize the IoT data and perform complicated analytics on the data from various IoT devices. IBM uses cognitive computing to extract valuable insights from structured and unstructured data and help users to understand the data better. IBM Watson provides Natural Language Processing, Machine Learning, and image and text analytics to enrich IoT apps.
Cisco Data Analytics
With Cisco Data analytics it’s easy to run analytics applications in the entire network from the cloud to the fog. Cisco provides infrastructure and tools for businesses to perform analytics on the collected IoT data. Cisco IOx APIs helps companies to make the data available to the internal applications to improve operational efficiency. Cisco IoT analytics infrastructure offers:  Infrastructure for Real-time Analytics, Cloud to Fog, Enterprise Analytics Integration and Analytics for Security
Oracle Stream Analytics and Oracle Edge Analytics
Oracle’s IoT Analytics solution is a combination of both Oracle Stream Analytics and Oracle Edge Analytics. Oracle’s solutions help you to develop analytics application which can read and analyze data from various sensors and devices and provide valuable insights. Both Stream Analytics and Edge Analytics can process and analyze huge volumes of streaming data collected from sensors and devices.
Conclusion
Implementing the right analytics solutions either by purchasing off-the shelf IoT solution or outsourcing the development of cloud based analytics solution is critical for the success of an IoT project. Are you going in the right direction? Is your IoT application providing you with the right insights? Contact us and book a free session with our experienced IoT consultants and we will help you to derive the best value out of your IoT implementation.