10 IoT Data Analytics Platforms Solution Providers Can Use At The Edge

Data Analytics For IoT

Over the past few years, the Internet of Things has consisted of companies connecting their devices. But as the IoT market matures, more customers are looking beyond connectivity services at the data that is actually running through their devices.

Analytics tools are playing a bigger part in IoT, from industrial companies that want to collect, monitor and analyze data from their machines, to health-care professionals who want to view real-time patient data.

Most vendors at this point have developed analytics tools for the edge – including Intel, Microsoft and Amazon Web Services. Here are 10 IoT data analytics platforms that solution providers can use to optimize their IoT solutions for customers.

Azure Stream

Microsoft's existing IoT platform includes various data analytics offerings like Azure Stream Analytics and IoT Central, a service that can deploy and manage a company's IoT ecosystem from devices to cloud.

Azure IoT Edge, released this spring, fills a final gap in the company's real-time analytics capabilities. Microsoft's platform with Azure IoT Edge helps IoT devices run cloud services, process data in real time and communicate with sensors and other connected devices, even with intermittent cloud connectivity.

Intel Analytics Toolkit

Intel's IoT platform includes resources for the collection and analysis of sensor data, which the Intel IoT Developer Kit provides. Intel's beta cloud-based analytics system for IoT includes resources for the collection and analysis of sensor data. Customers using this service can jump-start data acquisition and analysis without having to invest in large-scale storage and processing capacity.

Dell Statistica

Dell has approached IoT analytics from the edge with its Statistica tool, with features like edge scoring for IoT analytics, collective intelligence and native distributed analytics architecture (NDAA). The latest release of Statistica, version 13.1, came out in 2016 with new capabilities that Dell said are designed to empower data scientists, enable organizations to better address growing IoT analytics requirements, and leverage heterogeneous data environments. Statistica also features network analytics capabilities that enable users to combine the power of predictive analytics with human expertise to better detect fraud and understand relationships within complex networks.

AWS

AWS' GreenGrass builds off AWS IoT and AWS Lambda – a "serverless" compute service that enables users to run "stateless" code on servers so that it isn't attached to any particular infrastructure and will always run when triggered.

The newest AWS service enables developers to write Lambda code that can run straight from the edge, and is built for offline operation so that IoT data can continue to be processed even when connectivity to the cloud is temporarily unavailable.

SAP HANA

SAP's cloud-based analytics platform features pre-integrated and open IoT capabilities. These features are based on the HANA cloud platform, and provide smart data streaming, remote data synchronization, IoT services for device message management and IoT application services to cloud-based environments.

SAP also offers Streaming Lite, a small-footprint version of its data analytics engine that enables customers to deploy on devices closer to the edge.

IBM Watson

IBM's IoT analytics platform is part of its larger Internet of Things Watson platform. The Watson analytics services enable users to leverage cognitive analytics with structured – and unstructured – data to understand situations, look at options and learn as conditions change. Users gain access to Watson natural language processing, Watson text analytics, Watson video and image analytics, and Watson machine learning tools.

Cisco Connected Streaming Analytics

Cisco touts its connected streaming analytics platform, which streams live data from multiple sources for real-time insight with big data views. The CSA platform features distributed and tiered options to deliver horizontal scale and localized data processing, as well as high-performance, real-time analytics with low latency.

Oracle Edge Analytics

Oracle's analytics platform is made up of two parts – the Stream Explorer, which collects data in the cloud or enterprise, and Edge Analytics, which filters and aggregates data on embedded devices. These two tools enable out-of-the-box analytics that detects patterns in streams for vertical markets in particular.

PTC

PTC's ThingWorx Analytics, which the company touts as part of its larger IoT platform, enables developers to detect real-time patterns and anomalies, as well as predictive analytics, in the solutions they build. ThingWorx also provides web and mobile application enablement and runtime capabilities, providing rapid development of role-based user experiences.

HPE

HPE's Edgeline Services Platform is a software foundation that enables partners to deliver analytics services at the edge for connected operational technology devices – which include industrial control systems like programmable logic controls or SCADA systems.

One part of the platform, the HPE Edgeline data aggregation app, is an operational technology software app that combines data from multiple operational technology devices, and aggregates it together in a single data collection.