全面的实时决策与行业领先的分析相结合。
简化的分析模型部署
提供用于访问和管理信息、选择分析模型以及定义用于创建生产使用环境的业务规则的通用方法。
实时分析
将实时分析和业务规则应用于历史数据，以便在客户交互和运营业务流程期间立即获得洞察和建议的最佳操作。
快速决策流程的创建和管理
实现对不断变化的决策和客户动态的快速响应。易于使用的管理控制台让您可以使用可重复使用的拖放式节点来构建复杂的决策式流程图，并将流程与数据源和分析链接起来。
通用决策创作和部署环境
简化整个决策流的验证。完整的版本控制可在 IT 和业务共享的环境中保留文档、测试可追溯性和连续性。
友好的用户界面
通过可重复使用的开箱即用型任务、来自现有存储库中的数据和模型选择以及共享的、灵活的处理控制逻辑，实现直观的决策流程设计。
集成 SAS 机器学习功能
使用自动注册来集成模型开发。加速常见的手动任务，例如业务规则定义和部署。通过公共模型存储库促进集中的模型管理和监控。
改善与客户、合作伙伴、供应商和员工的互动。
自动并大规模地做出正确决策。
根据自动化、复杂的分析来提供相关的、交互式决策。IT 和商业用户可以使用当前和历史操作数据（由分析模型提供信息并受业务规则管理）来共同设计和部署运营决策，这些决策可以针对成千上万的每日决策自动、大规模地定义实时最佳行动。从直接的、面向客户的决策（例如，产品定位和信用决策）到诸如制造等领域的复杂、跨职能的决策，您可以相信企业决策是高效、有效和及时的。
标准化分析模型部署。
通用的决策创作和部署环境可以极大地减少 IT 验证和部署分析模型所需的时间，无论是使用 SAS、开源还是自定义代码编写而成的。您可以借助同时适用于批处理和实时 Web 服务执行的相同逻辑，从单一界面本地集成、管理和部署 SAS 和 Python 分析模型、自定义代码和业务规则。这意味着更快的部署和对分析驱动运营决策完整性的信心。
在大批量环境中做出高质量的决策。
无论您的数据和决策量有多大；您将始终能够在需要时准确地做出最佳的运营和客户决策。无需担心在批量巨大时缓慢、停止响应的计算资源会造成决策延迟。我们的解决方案基于具有服务器聚类功能的多层架构，可提供可伸缩性和企业数据吞吐量，以及时、准确地做出决策，即使在大批量的 24/7 业务中也是如此。
直观地设计决策流程。
不是技术专家？不是也没问题。直观、友好的用户界面让您无需 IT 协助即可轻松构建和修改自动决策流程，甚至是合并 SAS 分析模型。您可以通过拖放一组可重复使用的开箱即用型任务来设计流程，而不必使用令人费解的编程和规则。共享的、灵活的处理控制逻辑让您能够从现有存储库中选择数据和模型。通过在上下文环境中定义业务规则，确保业务功能之间的连续性和术语共享。
这款最新推出的解决方案在现代开放式平台SAS Viya上运行，可在广度和深度两方面轻松应对任何分析方面的挑战。SAS Viya是一个基于云平台的统一环境，可以被数据科学家、业务分析师、应用程序开发人员和管理人员等使用。它具有稳定可靠、可扩展、安全管理管控等一系列敏捷IT所必需的特性。全球分析领域领导者 — SAS满足您对系统性能的要求。
探索 SAS® 智能决策和其他产品的更多信息
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E-Book
Brilliant decision? In the battle for consumers’ hearts and minds, retailers have typically focused their digital transformation initiatives on customer experience and engagement. However, in these challenging times, it’s not enough to just get the customer’s attention — you need to convert impressions and site or store visits into sales and fulfilled orders.
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Customer Story
Building customer satisfaction with better network monitoringSAS Analytics helps a major telecom organization analyze traffic, anticipate problems and improve customer service.
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White Paper
Operationalizing and Embedding Analytics for ActionThis TDWI Best Practices Report focuses on how organizations can and are operationalizing analytics to derive business value.
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White Paper
Marketing attribution: Giving credit where credit is dueMarketing attribution helps you analyze the impact and business value of company-generated marketing interactions to help make the best marketing investment decisions. The challenge is to interpret the massive volumes of customer data that continues to expand day by day.
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Article
Real-time customer engagement is the future of experience managementReal-time customer engagement delivers contextual recommendations and decisions to your interactive customer channels at every possible touch point.
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White Paper
The Internet of Things: Marketing’s Opportunities and Challenges Learn how marketers can apply event-based marketing and real-time marketing capabilities to capitalize on IoT data in the moment by pinpointing significant customer events, which then trigger real-time customer decisions. The result? Best offers delivered in real time, given the consumer’s current context.
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Article
Three ways to improve real time marketing resultsReal-time marketing enables you to reach customers during purchase deliberations to provide the push a campaign needs be wildly successful.
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White Paper
Managing the Analytics Life Cycle for Decisions at ScaleLet the SAS Analytics Life Cycle guide you through the iterative process of going from raw data to predictive modeling to automated decisions, faster. This paper tells you how.
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Customer Story
Better customer service via machine learningAdvanced analytics helps Rogers Communications become more customer-centric, cutting customer complaints in half.
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White Paper
Real-Time Analytics: The Key to Unlocking Customer Insights & Driving the Customer ExperienceThis Harvard Business Review Analytic Services report looks at how businesses are using advanced customer data analytics, along with real-time analytics and real-time marketing, to enhance their customers’ experiences.
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Article
Effective real-time marketingEffective real-time marketing is about engaging with customers whenever and wherever they are in their buying journey. Organizations should also be focused on knowing what the customer wants (product, pricing, experience, etc.) based on real-time analytics and predictive modeling.
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White Paper
Six Keys to Credit Risk Modeling for the Digital AgeModernizing and automating the end-to-end process for origination and servicing – from data management to model development to credit decisions – can reduce credit losses and boost performance. This paper explores how infusing machine learning into this process supports more effective credit decisions for individuals, products or portfolios.
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Article
IoT: The customer experience accelerator you can't afford to ignoreIoT represents a powerful source of data that, when combined with analytics, can yield insights on everything from behavior to emotions to health. And that's why it's key to improving customer experience.
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Customer Story
AI-driven personalization gives electronics retailer a boostConrad Electronic uses customer intelligence solutions from SAS to craft relevant offers in real time.
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Customer Story
Hybrid approach ensures seamless experience for insurance customersInsurance company Topdanmark gains a true omnichannel marketing approach and better workflows with SAS® Customer Intelligence 360.
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Customer Story
Personalization is key in telecommunications. And analytics the natural solution.Telenor Norway uses SAS Analytics to enhance business decisions and continuously adapt to customers’ needs.
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Analyst Report
SAS is a Leader in The Forrester Wave™: Real-Time Interaction Management, Q4 2020Forrester names SAS a Leader in The Forrester Wave™: Real-Time Interaction Management, Q4 2020.
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