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SAS & Amazon Web Services

Enterprise organizations are making strategic decisions on how to best leverage their data and analytic investments. SAS and AWS are uniquely positioned to support these efforts. SAS on AWS allows organizations to deploy open source and SAS models into production quickly (ModelOps), while scaling the infrastructure needed to support the wide variety of analytic compute patterns (DevOps). This combination provides an agile and integrated platform to turn data into actionable insights, helping new and existing users make better decisions that benefit their businesses and their customers.

New Workloads

  • Leverage the scalability of AWS services and SAS Viya to put analytic capabilities in the hands of users across the organization through visual interfaces
  • Allow users to integrate with open-source technologies within a single, flexible environment
  • Deploy sandbox environments quickly to test new ideas and lower the cost of experimentation using AWS Quick Start for SAS Viya
  • Deploy SAS closer to AWS datastores like Redshift, EMR and Aurora to ensure optimal performance and I/O throughput.
     

Existing Workload

  • Migrate SAS on-premises workloads to gain flexibility and cost-effectiveness
  • Leverage tested deployment patterns from best practices to remove friction related to migrating workloads
     

Integrations

  • Target optimal performance through testing of SAS with various EC2 instances, storage environments, and file systems
  • Ensure a simplified end-to-end environment, without the need to integrate and manage numerous point solutions

Industry
Banking & Financial Services, Capital Markets, Communications, Education, Energy & Utilities, Government, Health Care, Life  Sciences, Insurance, Manufacturing

Focus Area
Analytics, Big Data, Data Management, Cloud Computing, Customer Intelligence and Advertising

Specialization
Cloud Computing

Initiatives

SAS Viya on AWS
By bringing SAS Viya to the world's most broadly adopted cloud platform, SAS and AWS will help organizations of every kind make faster, trusted decisions and maximize their investments in data management, machine learning and AI. SAS and AWS are working together to help customers optimize their use of SAS on the AWS cloud. Read more at AWS and SAS | SAS

SAS and AWS for Marketing and Customer Engagement
Accelerating digital transformation efforts are emphasizing the need to simplify complex, siloed, and underperforming MarTech ecosystems. An enterprise marketing solution that runs on Amazon Web Services, SAS Customer Intelligence 360 focuses on intelligent and purpose-driven marketing. Using dynamic data collection technology, SAS Customer Intelligence 360 enables brand marketers to gain a holistic view of all components of the individual customer journey. With SAS Customer Intelligence 360, marketers can use the data that belongs to their brand to identify key customer insights and convert this knowledge into more relevant, targeted, and individualized communications on all marketing channels- both digital and direct. This results in improved time-to-market for customer data activation and engagement activities, all while adhering to privacy, transparency, and trust requirements. With a modern, AI-powered, multichannel marketing hub, brands can flexibly create personalized journeys, while effectively leveraging resources and maximizing impact. Additionally, SAS and AWS provide the scalability needed to help brands mature over time by increasing data and analytics usage and expanding channel activation capabilities. Read more at sas.com/marketing

Discover how SAS is revolutionizing the marketing landscape with its Customer Intelligence 360 platform, powered by AWS generative AI capabilities.

Resources

Experian Customer Video
Experian leverages the scalability and durability of AWS to deliver SAS analytic capabilities.

Experian leverages SAS Viya and Amazon EMR to solve three problems.

  • Data scalability – being able to use in-memory processing with horizontal scalability
  • The ingestion of large data volumes from Hadoop
  • Support for Open Analytics coding including R and Python

Success Story
CNM is strengthening communities by leveraging SAS Analytics on AWS

Nonprofit consulting firm CNM uses SAS® Visual Analytics on Amazon Web Services to help other nonprofit organizations measure and communicate the impact of their work. Read full story.

Success Story
T-Mobile realizes $1.5M in annual savings and increases the speed of SAS Grid workloads using Amazon FSx for Lustre

Looking to increase scalability while reducing costs, T-Mobile enlisted the support from Core Compete, a SAS Gold Partner, to deploy their SAS grid workloads Amazon Web Services. The results exceeded expectations.

Success Story
Orlando Magic grows single game ticket revenue by 91% using an Analytics and Machine Learning Platform from SAS and AWS.

Orlando Magic achieved this using SAS® Visual Analytics, SAS® Visual Statistics and SAS® Visual Data Mining and Machine Learning powered by SAS® Viya® on Amazon Web Services.


About Amazon Web Services

For 17 years, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud platform. AWS offers over 165 fully featured services for compute, storage, databases, networking, analytics, robotics, machine learning and artificial intelligence (AI), Internet of Things (IoT), mobile, security, hybrid, virtual and augmented reality (VR and AR), media, and application development, deployment, and management from 99 Availability Zones (AZs) within 31 geographic regions, spanning the U.S., Australia, Brazil, Canada, China, France, Germany, Hong Kong Special Administrative Region, India, Ireland, Japan, Korea, Singapore, Sweden, and the UK. Millions of customers including the fastest-growing startups, largest enterprises, and leading government agencies—trust AWS to power their infrastructure, become more agile, and lower costs. AWS is guided by four principles: customer obsession rather than competitor focus, passion for invention, commitment to operational excellence, and long-term thinking. To learn more about AWS, visit aws.amazon.com.