How SAS Viya Workbench on AWS accelerated analytics innovation

By: Doug Mbaya, Sr Partner Solutions Architect – AWS
By: Dmitry Frizner, Solutions Architect – AWS
By: Erin McCarthy, Senior Product Marketing Manager – SAS

SAS

Data scientists and developers today need to deliver insights faster while managing growing data volumes and meeting compliance requirements. SAS Viya Workbench on Amazon Web Services (AWS) helps accelerate analytics innovation by providing a cloud-centered environment where your team spends less time managing infrastructure and more time building models. If environment configuration, version conflicts, and security approvals are slowing your analytics projects, this solution offers a path forward.

In this post, we explore how SAS Viya Workbench on AWS addresses these challenges through its split-plane architecture, examine real-world use cases across industries, and show you how to get started.

Meeting developers where they are

Working across multiple languages and frameworks such as Python notebooks, R scripts, SAS procedures, and SQL-based workflows creates real obstacles when these tools run on disconnected local machines or legacy infrastructure.

Every environment needs its own infrastructure, security controls, software versions, and data access. Spending valuable time on managing these elements means neglecting more important work. Data scientists often spend hours installing software, resolving version conflicts, and configuring machines when they could be exploring data and generating insights.

Limited access to tools or environments, incompatible workflows, and slow approval processes create barriers to collaboration. Teams resort to emailing files or manually transferring datasets. The lack of a single, shared workspace leads to version mismatches and broken code.

Maintaining robust security and properly complying with regulations is essential, but the process of doing so can slow teams down. They might have to wait days or weeks for IT to approve new tools and infrastructure. But if they bypass controls, they put the organization at risk.

Many software professionals use standard laptops for work. But with fixed memory and processing power, such tools can cause crashes or force analysts to work with only a small sample of the data when demands spike.

Traditional approaches, including maintaining separate environments for each language, manually provisioning compute resources, or relying on desktop installations, struggle to address these challenges together. They typically solve one problem while creating others, forcing tradeoffs between flexibility, security, and scalability.

How SAS Viya Workbench on AWS addresses these challenges

AWS has partnered with SAS to bring SAS Viya Workbench to AWS Marketplace. This unified analytics environment reduces these tradeoffs by offering flexibility in programming languages, cloud scalability, and data custody.

SAS Viya Workbench offers a choice of languages. Your team can work in Python, R, and SAS within a single cloud-based environment, without having to switch between tools or manage separate installations.

By integrating with Amazon Simple Storage Service (Amazon S3), Amazon EMR, and Amazon Redshift, SAS Viya Workbench provides elastic compute that grows with your workload.

You maintain custody of your data within your AWS account. SAS manages only the control plane for orchestration.

With a few clicks, your team can provision fully managed development environments that are secure, collaborative, and optimized for modern analytics workloads.

Understanding the split-plane architecture

Traditional analytics solutions often force a choice between security and flexibility. SAS Viya Workbench addresses this tradeoff through a split-plane architecture.

Before diving into the benefits, review the functions of the control plane and data plane:

• Control plane handles management functions such as user authentication, environment configuration, and orchestration.
• Data plane processes your actual workloads, running queries, training models, and storing results.

The separation of the control plan and the data plane delivers specific advantages for your organization. Your AWS account contains all compute resources, data storage, and processing engines. Your data doesn’t leave your environment, so you maintain data custody. SAS handles environment orchestration, user management, and service coordination through the SAS-managed control plane, without accessing your data. Your stakeholders in your organization benefits from SAS analytics expertise, while your security team maintains full visibility and control. Connectivity between planes is encrypted with TLS for secure communication without sacrificing performance.

By using this design, your organization maintains control over data and compute resources while benefiting from SAS’s advanced analytics and AI capabilities.

The solution addresses enterprise security requirements through comprehensive protections. All customer data remains within your AWS account, maintaining data sovereignty. End-to-end encryption protects data in transit and at rest. Granular role-based access controls integrate with AWS Identity and Access Management (IAM) and third-party identity providers. Comprehensive logging and monitoring support compliance requirements, with adherence to industry standards including AWS System and Organization Controls (SOC) 2, General Data Protection Regulation (GDPR), and Health Insurance Portability and Accountability Act (HIPAA).

The following diagram shows the SAS Viya Workbench split-plane architecture.

Figure 1: SAS Viya Workbench architecture diagram

Real-world use cases

Organizations across industries are applying this approach to accelerate their analytics initiatives.

In life sciences, cross-functional research teams analyze genomic data at scale using R and SAS in the same environment. One research organization reduced environment configuration time significantly, which freed scientists to focus on analysis rather than infrastructure setup.

Financial services firms improve fraud detection pipelines by integrating Python-based machine learning (ML) with SAS regulatory models. Risk teams maintain compliance while accelerating model development cycles.

Manufacturing operations teams optimize supply chains through real-time analytics pipelines using Amazon S3 and Amazon EMR. When demand forecasting requires additional compute resources, the environment scales automatically rather than requiring manual intervention.

Marketing analytics enhance customer segmentation and campaign effectiveness through integrated multichannel data analysis and predictive modeling.

Retail analytics teams create personalized shopping experiences and optimize inventory through advanced demand forecasting and customer behavior analytics, combining multiple data sources in unified workflows.

Enhancing developer productivity with Workbench

Now that you understand the architecture, let’s examine how SAS Viya Workbench improves daily workflows.

Built-in Git support means that developers can collaborate with each other, track changes, and maintain quality code without leaving the environment. Prebuilt templates for Python, R, and SAS models and workflows reduce development time from weeks to days because teams start with proven patterns rather than blank screens. The browser-based integrated development environment (IDE) eliminates local setup and configuration, so developers can launch code, test models, and deploy from their preferred browser. Automatic self-termination shuts down idle sessions after a specified period, helping manage computing costs efficiently.

With infrastructure management handled by the environment, your team focuses on building, training, and deploying models, whether using R for statistical modeling, Python for ML, or SAS for regulatory reporting.

The following table summarizes the key benefits:

Why this matters for your organization:

• Democratized analytics access – SAS Viya Workbench provides an intuitive, web-based interface for technical users and data scientists who prefer a code-first approach. Teams work with preferred programming languages while maintaining consistency in governance and deployment.
• Elastic scalability – The environment takes advantage of the elasticity of AWS and automatically scales compute resources based on workload demands, supporting optimal performance during peak usage and minimizing costs during idle periods.
• Accelerated time-to-value – Teams can start analyzing data immediately because of the pre-configured environments and extensive example libraries. They can use existing Python, R, or SAS code with minimal modifications, start from prebuilt templates, or code from scratch.
• Collaborative innovation – Built-in collaboration features support project teamwork, insight sharing, and model deployment. Version control, project templates, and shared computing resources foster innovation while maintaining reproducibility.

Conclusion

SAS Viya Workbench on AWS combines the analytical power of SAS with the scalability and security of AWS infrastructure. The split-plane architecture addresses data security and sovereignty concerns while providing collaboration and scalability benefits of cloud-based solutions.

For organizations that want to modernize analytics capabilities, this solution offers a compelling path forward that focuses on generating insights rather than managing infrastructure. At the same time, they maintain the necessary enterprise-grade security and compliance.

Get started today

Explore SAS Viya Workbench in AWS Marketplace to see how your team can:

• Collaborate securely across Python, R, and SAS
• Scale analytics workloads on demand
• Speed up model development and deployment

Contact your AWS account team or visit the SAS Viya Workbench listing in AWS Marketplace to learn more.

We’d love to hear about your analytics modernization journey; share your experiences in the comments section.

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SAS – AWS Partner Spotlight

SAS  is an AWS Advanced Technology Partner and AWS Competency Partner and the founder and future of analytics, harnessing the power of data and AI to shorten the path from questions to answers. The result is solutions like SAS® Viya® Workbench and SAS Customer Intelligence 360 that deliver productivity, performance and trust to help our customers make better decisions, faster

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