Built for speed
Engineered for high-volume processing of millions of events per second and low-latency response times. Outperforms other ESP engines.
Use machine learning and streaming analytics to uncover insights at the edge and make real-time, intelligent decisions in the cloud.
Ingests & consolidates streaming IoT sources
Extensive suite of prebuilt connectors and adapters lets you consume today's IoT sources – including structured and unstructured data streams – and extend in the future.
Ready for real-time action
Customizable alerts, notifications and updates provide situational awareness so you can react appropriately to what's happening or predicted to happen.
Flexible, open modeling environment
Intuitive visual interface makes it easy to define, test and refine models – no need for specialized programmers. Access coding environments via the interface. Python developer interfaces support design using familiar interfaces (e.g., Jupyter notebook).
Complete multiphase analytics
Embed SAS at the edge, in the fog and in data at rest, cleansing and analyzing data at each streaming event phase. In-depth SAS models are portable to the stream and the edge. Supports algorithms for vector data description, robust principal component analysis, random forest, gradient boosting and streaming regression analysis.
Image & video analytics
Combines streaming analytics, video and image ingestion with powerful neural networks to process video and still image data, including image pre-processing and object detection and classification.
Cloud ready
Compatible with cloud technologies, including BOSH Cloud Foundry, for large-scale distributed services. Ensures continuous, secure and stable event pattern detection through patented 1+N way failover, guaranteed delivery without persistence, full access to event stream model metadata, live stream queries and dynamic streaming model updates.
In-stream learning model windows
Use different window types – Train, Score, Calculate, Model Supervisor, Model Reader – for different tasks (e.g., specifying data stream input sources, patterns of interest and derived output actions).
Unified project deployment and server management
Use SAS Event Stream Manager to construct and manage reusable deployment templates, easily add new ESP servers, load and unload ESP projects, and automatically discover new servers using ESP agent technology for automated monitoring. When ESP servers are offline or unavailable, retry capabilities support redeploying models when connectivity resumes.
Seize opportunities and spot red flags hidden in torrents of fast-moving data flowing through your business.
Use machine learning to gain insights for taking the right action.
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.
Make sound big data decisions.
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.
Scale economically from edge to enterprise for growing data volumes.
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 simplifies and automates deployments.
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.
FEATURED PARTNER
Cisco & SAS
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.
Explore More on SAS® Event Stream Processing & Beyond
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Analyst Report
SAS takes Event Stream Processing to Cisco's edge for Internet of Things stackSAS and Cisco work together to enable IOT type analytics from the edge of the network to the data center to the cloud, according to 451 Research.
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Analyst Report
Bloor InBrief: SAS Event Stream ProcessingLearn why Bloor considers SAS a major contender in the market for streaming analytics platforms due to SAS’ differentiating analytic capabilities, notable performance and continuous improvement of in-stream models using machine learning.
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Analyst Report
Bloor Market Update: Streaming AnalyticsLearn why Bloor considers SAS a major contender in the market for streaming analytics platforms due to SAS’ differentiating analytic capabilities, notable performance and continuous improvement of in-stream models using machine learning.
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Analyst Report
How Data Science Teams Leverage Machine Learning and Other Advanced AnalyticsGartner's 2017 customer reference survey for data science and machine learning platforms reveals how many organizations are undertaking data science initiatives.
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Analyst Report
Top Strategic IoT Trends and Technologies Through 2023In this report, Gartner examines 10 longer-term IoT technologies and trends that will be important in the 2018 through 2023 time frame.
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Analyst Report
SAS is a Leader in The Forrester Wave™: Streaming Analytics, Q3 2017Streaming analytics are critical to building contextual insights for IoT, mobile, web and enterprise applications. Read the report to learn more.
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Article
The opportunity of smart grid analyticsWith smart grid analytics, utility companies can control operating costs, improve grid reliability and deliver personalized energy services.
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Article
Three C’s of the connected customer in the IoTTo optimize the connected customer experience, Blue Hill Research says organizations should build an IoT model based on three key features.
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Article
IoT in healthcare: Unlocking true, value-based careGiven the potential of IoT – and the challenges of already overburdened healthcare systems around the world – we can’t afford not to integrate IoT in healthcare.
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Customer Story
Artificial intelligence and IoT analytics keep aircraft operational for crucial missionsLockheed Martin revolutionizes aircraft maintenance with the SAS Platform.
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White Paper
Data Analytics at the Edge451 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.
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Customer Story
Finding the next football star with artificial intelligenceDutch sports analytics company SciSports uses emerging tech to innovate on the pitch.
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White Paper
The Autonomous Grid in the Age of the Artificial Intelligence of ThingsExplore how AI and IoT work together to deliver everything from improved threat detection to better customer engagement for utilities.
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White Paper
TDWI Checklist Report | Six Best Practices to Ignite the Customer Experience with IoTThe 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.
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White Paper
The Artificial Intelligence of Things 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.
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White Paper
Using Hybrid Cloud Capabilities for True Omnichannel MarketingSeamless, 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.
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White Paper
Capitalizing on Sensor Data OpportunitiesFind 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.
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White Paper
Drive Next-Generation Customer Experiences with Real-Time Connected Product and Service Analytics 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.
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White Paper
The Evolution of AnalyticsLearn 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.
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White Paper
Drive Next-Generation Performance With Real-Time Connected Manufacturing 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.
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White Paper
Intelligent Analytics for Smart Machines 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.
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White Paper
IoT Analytics in Practicethis paper will help business decision makers make informed investment decisions about the future of their own IoT analytics projects
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White Paper
Prescriptive Analytics: Just What the Doctor OrderedInefficiency, 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.
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White Paper
Securing Your IoT Solution StackLearn 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.
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White Paper
Analytics Accelerates Monetization Opportunities for Connected Vehicle and Mobility ServicesLearn 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.
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White Paper
Channeling Streaming Data for Competitive AdvantageDiscover 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.
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White Paper
Understanding Data Streams in IoTThis 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.
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Analyst Report
Bloor InBrief: SAS Event Stream Processing Bloor InBrief: SAS Event Stream Processing
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White Paper
The Connected InsurerExplore 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.
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White Paper
How Streaming Data Analytics Enables Real-Time DecisionsLearn how SAS provides extremely high-throughput, low-latency technology to meet whatever streaming analytics your company might want to pursue.
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Customer Story
Increasing customer loyalty with artificial intelligenceConnexions Loyalty Chief Data and Analytics Officer turns streaming customer data into a source of innovation.
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Customer Story
IoT data with artificial intelligence reduces downtime, helps truckers keep on truckingVolvo Trucks and Mack Trucks use sensor data and SAS AI solutions to minimize unplanned downtime.
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