Rise to a higher level of clarity
As the market leader in analytics, SAS empowers organizations to create and sustain true value from diverse IoT data and initiatives – whether your data is at the edge, in motion or at rest. Its robust, scalable and open edge-to-enterprise platform bridges IT and operational environments, while spanning the entire IoT analytics life cycle – from data capture and integration to analytics and deployment. From visualization and statistical modeling to descriptive, predictive and prescriptive analytics, SAS delivers deep expertise in IoT analytics – including AI, machine learning and deep learning – to help you reduce risk and gain real business value. SAS Analytics for IoT enables you to make fast, confident decisions – while reducing data transport and storage costs.
The SAS Event Stream processing engine can handle huge volumes of data at very high rates (e.g., millions per second), with extremely low latency (in milliseconds). This enables real-time data management for IoT devices, networks and usage data, making your IoT data analytics-ready. Intelligent filtering separates what’s relevant for your business from all the noise so you’ll know what data to store and what you can ignore.
Get the most out of IoT data by mining and analyzing it where it lives – edge devices, data centers or the cloud. And detect patterns of interest as events occur. With SAS Analytics for IoT, you can integrate, transform, visualize and analyze IoT data throughout the connected ecosystem. Then close the IoT analytics loop by running big data analytics on data at rest.
You can continuously assess streaming data close to its origination, transforming and analyzing it in real time. SAS decision management capabilities then drive real-time action – from simple alerts to complex, automated responses. SAS Analytics for IoT supports data integration, visualization and analytics at the edge, as well as big data analytics on data at rest in the storage platform of your choice.
Advanced analytics solutions with embedded AI and machine learning enable you to analyze a variety of structured and unstructured IoT data sources. Choose from a huge array of SAS and open source machine learning and high-frequency analytics to understand streaming data and gain insights you can act on immediately.
Combining streaming data with advanced analytics and AI reveals patterns that empower real-time decisions. Advanced analytics and mathematical algorithms are developed using rich histories of stored data that can be encoded into data streams, enabling continuous scoring of streaming data.
Consume streaming big data as close to the edge as you need. Embedded data quality routines and text processing execution means big data is filtered and ready to consume. Prebuilt connectors and adapters let you write once and deploy anywhere – today and into the future.
Powerful, optimized edge computing combined with machine learning enables high-volume throughput of millions of events per second, and low-latency response times. Distributed, in-memory grid processing running in commodity hardware environments can scale linearly as your data grows.
Explore how IoT analytics solutions from SAS are using AI to help a variety of industries get the most out of IoT data – unlocking new revenue streams, operational efficiencies and differentiated customer experiences.
Bring together data, analytics and marketing processes to gain an omnichannel view of your customers across all devices.
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