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.
Get to Know SAS® Event Stream Processing
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- Analyst Report SAS is a Leader in The Forrester Wave™: Streaming Analytics, Q2 2021Forrester says, "SAS Event Stream Processing (ESP) stands out in this evaluation as the platform with the most built-in analytics for machine learning and other advanced analytics."
- Article 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.
- Analyst Report Bloor InBrief: SAS 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.
- Article Components of an information management strategyBefore starting a data management strategy for your business, you need to understand each component. Data expert David Loshin breaks them down.
- Article How openness can supercharge event stream analyticsWhat does openness do for event stream analytics? David Loshin shows how it helps you speed and govern the full streaming analytics life cycle.
- Customer Story Real-time analytics helps telecom provider adapt to changing customer needs during global pandemic and beyondTelefónica Ecuador accelerates digital transformation, improves campaigns and achieves growth via intelligent decisioning powered by SAS.
- Analyst Report SAS: Providing a Comprehensive Approach to the IoT Analytics Life CycleThis IDC Vendor Profile offers IDC's perspective on the IoT strategy of SAS.
- Customer Story Transforming steelmaking through IoT analyticsSSAB improves production efficiency, product quality and maintenance strategies using sensor data, artificial intelligence and advanced analytics.
- Article The opportunity of smart grid analyticsWith smart grid analytics, utility companies can control operating costs, improve grid reliability and deliver personalized energy services.
- White Paper IoT Analytics in PracticeIoT, Analytics
- 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.
- 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.
- 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.
- 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.
- 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.
- 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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