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SAS Event Stream Processing
Analyze streaming data, uncover hidden insights with AI and make real-time, intelligent decisions in the environment of your choice.
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 cloud 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.
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Key Features
Use machine learning and streaming analytics to uncover insights at the edge and make real-time, intelligent decisions in the cloud.
Built for speed
Enables high-volume processing of millions of events per second and low-latency response times using newly integrated ONNX Runtime for expanded support for GPU acceleration on CUDA and TensorRT supported platforms.
Ingests & consolidates streaming IoT sources
Lets you consume today's IoT sources – including cloud or edge on-site streams – and extend in the future with an extensive suite of prebuilt connectors and adapters.
Ready for real-time action
Provides you with situational awareness via customizable alerts, notifications and updates so you can react appropriately to what's happening or predicted to happen.
Flexible, open modeling environment
Easily define, test and refine models in a low code environment using an intuitive visual interface. Data scientist-friendly coding environments include familiar Python developer (e.g., Jupyter notebook).
Complete multiphase analytics
Embed SAS at the edge, in the fog and in the cloud, cleansing and analyzing data at each streaming event phase. In-depth SAS models are portable to the stream and the edge. Supports algorithms, for example, to perform support vector data description, robust principal component analysis, random forest, gradient boosting and streaming regression analysis.
Unified project deployment & server management
SAS Event Stream Manager lets you construct and manage reusable deployment templates, easily add new auto-discover ESP servers in cloud, load and unload ESP projects, dynamically allocate resources, and automatically scale up and down for automated elasticity and monitoring for better resource management. When ESP servers are offline or unavailable, retry capabilities support redeploying models when connectivity resumes.
Cloud native
Compatible with cloud technologies, including Docker and Kubernetes, for large-scale, elastic, multitenant, distributed services. Ensures continuous, secure and stable event pattern detection through patented, instantaneous 1+N way failover, native failover, guaranteed delivery without persistence and other fault-tolerance functions for resilient, highly available event stream processing.
In-stream learning model windows
Uses 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).
Image & video analytics
Process video and still image data, including image pre-processing and object detection and classification, by combining streaming analytics, video and image ingestion with SAS and third-party machine learning frameworks using ONNX model formats.
Customer Success
Look Who's Working Smarter With SAS®
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Optimizing the supply chain with analytics and IoT
SAS is helping Georgia-Pacific improve equipment efficiency, reduce downtime, optimize shipping logistics and predict customer churn.
Get to Know SAS Event Stream Processing
Featured Partners
Wabtec, Intel & SAS
Wabtec, Intel and SAS are partnering to transform raw data into real-time business insight with IoT connected transportation – and unlock new levels of operational efficiency.
Explore More on SAS Event Stream Processing and Beyond
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- 고객 사례 Leading cruise line personalizes passengers’ onboard experience in real timeNorwegian Cruise Line Holdings uses SAS to transform onboard experiences for passengers with prompt personalized communications
- 고객 사례 One airport operator is making every journey personal for passengersiGA Istanbul Airport creates personalized customer journeys using SAS® MarTech solutions
- E-BOOK Rising Waters and Rapid ResponsesGet an insider’s view of the tools and strategies that some leaders in flood management are already deploying to better protect their citizens, as well as case studies that show how these approaches work in real-world applications.
- 분석 보고서 SAS named a Challenger in Gartner® Magic Quadrant™ for Augmented Data Quality SolutionsSAS named a Challenger in Gartner® Magic Quadrant™ for Augmented Data Quality Solutions.
- 웨비나 Real-Time Predictive Analytics: Uncovering Opportunities and Barriers at the Speed of Data FlowJoin us as we discuss how SAS® Event Stream Processing can help organizations uncover data anomalies instantly, before trouble starts or opportunity passes
- 분석 보고서 IDC Spotlight: Looking Beyond the AI Model to Improve the Value of Computer Vision in Manufacturing OperationsThis IDC Spotlight explores the increasing adoption of computer vision (CV) by manufacturers, and how in order to succeed, they must focus on more than just model development, validation and deployment. SAS delivers a comprehensive portfolio of tools, software and resources – integrated into SAS Viya – to develop and deploy CV solutions.
- 파트너사 요약정보 Streaming Analytics and Internet of ThingsUse AI and streaming analytics to uncover insights at the edge and make real-time, intelligent decisions in the cloud.
- 블로그 게시물 A conversation with Rijkswaterstaat: How SAS is helping keep the Netherlands safeIn a recent panel discussion, project leaders at RWS talked about some of their latest projects and how SAS is helping fulfill the RWS mission to keep the Netherlands’ waterways safe and efficient.
- 솔루션 요약 Analyze streaming data from edge to enterprise to make intelligent decisions in real time
- 기사 Real-Time Customer Recommendation Systems for Data in Motion
- 기사 Understanding data in motionLearn how to analyze fast-moving data streams on the fly with event stream processing.
- 기사 Sensing a disturbance in the dataAs IoT data unites with event stream processing (ESP), these combined forces will automatically sense data pattern deviations and trigger immediate response.
- 기사 Making sense of streaming data in the Internet of ThingsThe Internet of Things has changed our lives forever. Read about how streaming data in IoT works, and why it has caused such a shift in the analytics world.
- 고객 사례 Transforming steelmaking through IoT analyticsSSAB improves production efficiency, product quality and maintenance strategies using sensor data, artificial intelligence and advanced analytics.
- 고객 사례 World’s largest sports and humanitarian event builds legacy of inclusion with data-driven technologySpecial Olympics World Games Abu Dhabi uses SAS® Analytics and AI solutions to keep athletes safe and fans engaged.
- 백서 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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