Built for speed
Engineered for high-volume processing of millions of events per second and low-latency response times. Outperforms other ESP engines.
Streaming data from operations, transactions, sensors and IoT devices is valuable – when it's well-understood. Event stream processing from SAS includes streaming data quality and analytics – and a vast array of SAS and open source machine learning and high-frequency analytics for connecting, deciphering, cleansing and understanding streaming data – in one solution. No matter how fast your data moves, how much data you have, or how many data sources you’re pulling from, it’s all under your control via a single, intuitive interface. You can define patterns and address scenarios from all aspects of your business, giving you the power to stay agile and tackle issues as they arise.
Filter, normalize, categorize, aggregate, standardize and cleanse big data before you store it – saving significant staff and computing resources from having to clean up data lakes. Prebuilt data quality routines and text processing execution are applied to data in motion so big data is filtered and ready for consumption.
Faster, better, more powerful stream processing from edge to enterprise for high-volume throughput (millions of events per second) means low-latency response times running in distributed, in-memory grid processing commodity hardware environments. Analyze structured and unstructured data sources – including video, text, and image classification and identification – using advanced analytics with embedded AI and machine learning capabilities. In addition, SAS® Event Stream Manager integrates SAS Event Stream Processing studio and server components, simplifying and automating the deployment of SAS Event Stream Processing projects and analytics for rapid decision making – with no disruption to service.
SAS Event Stream Manager provides a repeatable, automated and traceable process to help you monitor, govern and track large groups of SAS Event Stream Processing servers. The solution works from edge to enterprise in the cloud, on-site or at the edge.
Cisco and SAS are partnering in several strategic areas to help customers modernize their analytics architectures. SAS® Analytics on the Cisco Unified Computing System™ (UCS) integrates high-velocity delivery of information in real time. The benefits that result from conducting proofs of concepts of SAS applications with Cisco technology include reliable scalability, reduced data center costs, and improved efficiencies that allow staff to focus on strategic business initiatives.
Inefficiency, unresolved problems and lack of innovation. These symptoms are often part of a larger organizational illness – one that likely originates with how data is managed. To achieve a cure, you need the right medicine: big data analytics.
Discover how and why innovative companies are transforming business operations by using streaming analytics to extract meaning from live data streams as data is created, and automate reactions to it with millisecond response times.
The IoT extends digital customer experience to physical customer experience and customer journeys for ultimate brand distinction. This TDWI Checklist Report, sponsored by SAS, outlines six best practices for data professionals and practitioners when using IoT to improve customer experience.
451 Research explores the value of diverse IoT data that is processed and analyzed at the edge in environments like T&D facilities, oil fields and manufacturing shop floors.
Find out who is using embedded sensors and how they are using them. This report explores how sensors can make manufacturers more competitive and provides guidance on using sensor-generated data as a flowing stream of opportunity rather than an unexpected flood that disrupts and distracts.
Learn how automakers and their partners are using IoT data and analytics to help them reshape business models, seize new sources of revenue and develop inventive ways to better serve customers.
Explore the opportunities IoT creates, the barriers to its adoption within the insurance industry, and what’s needed to fully exploit the potential of IoT for competitive advantage and growth.
This paper explains how streaming analytics helps you acquire, understand and use real-time, streaming data to make fact-based, automated decisions – and instantaneously react to new information.
Learn how SAS provides extremely high-throughput, low-latency technology to meet whatever streaming analytics your company might want to pursue.
SAS, Hortonworks and Intel can help you embrace technologies and processes to anticipate a wide range of customer needs, providing the foundation for next-generation customer experiences.
Explore how AI and IoT work together to deliver everything from improved threat detection to better customer engagement for utilities.
Learn how you can make the flood of IIoT data work for you with an end-to-end analytics platform that combines SAS expertise in analytics with Intel’s leading data center technology.
This special report sponsored by SAS, Intel and Hortonworks explores how manufacturers are capitalizing on the promise of the IoT, creating new value streams and revolutionizing the relationship with markets.
Learn why IoT solutions are so difficult to secure, what's needed to secure each layer of the IoT stack, and how SAS uses software like SAS Event Stream Processing to secure the applications layer.
Seamless, agile customer interactions require a marketing system that can collect data about a customer’s interactions and behavior across all touch points, regardless of underlying technology. Learn how SAS Customer Intelligence 360 lets you use both cloud and on-site channels and data to create an omnichannel marketing solution.
We’re living in a world that has more connected devices than humans. See how AI amplifies the value and potential of this fast-growing Internet of Things.
Learn about modern applications for machine learning, including recommendation systems, streaming analytics, deep learning and cognitive computing. And learn from the experiences of two companies that have successfully navigated organizational and technological challenges to adopt machine learning and embark on their own analytics evolution.
this paper will help business decision makers make informed investment decisions about the future of their own IoT analytics projects
Check out these products related to SAS® Event Stream Processing, all built on the powerful SAS® Platform.
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