SAS Viya Reviews & Product Details

What I like best about SAS Viya is how it combines the strength and reliability of traditional SAS with a modern, flexible environment. I appreciate the cloud-based structure, which makes it easier to access projects from different locations, and the integration of visual analytics with coding in SAS and Python. The interface is clean and intuitive, but still powerful enough for advanced modeling, including mixed models and large datasets. It feels scalable, efficient, and well-suited for both teaching and research environments. Review collected by and hosted on G2.com.

While SAS Viya is powerful, the transition from traditional SAS 9.4 can sometimes feel challenging, especially when certain procedures or workflows do not behave exactly the same way. Some advanced features require additional configuration or licensing, which can limit access depending on the setup. In addition, for new users, the interface and ecosystem can feel a bit overwhelming at first, particularly when navigating between different applications (e.g., Visual Analytics, Model Studio, programming). A smoother learning curve and clearer guidance for users migrating from earlier SAS versions would be helpful. Review collected by and hosted on G2.com.

What I like best about SAS Viya is that it combines powerful data analytics, machine learning, and visualization into one modern, cloud-based platform. It allows users to process large datasets quickly using scalable computing while supporting multiple programming languages like SAS, Python, and R, which makes collaboration easier across teams. I also like that it integrates the entire analytics workflow from data preparation to model deployment and monitoring into a single system, helping organizations work more efficiently while maintaining strong data governance and security. Review collected by and hosted on G2.com.

One potential downside of SAS Viya is that it can have a steep learning curve, especially for users who are new to SAS or enterprise analytics platforms. The cost of licensing and implementation can also be high compared with some open-source alternatives, which may limit accessibility for smaller organizations. Additionally, while Viya supports multiple programming languages, some advanced customization can still feel more seamless within the SAS ecosystem, which may reduce flexibility for teams that primarily work in open-source environments. Review collected by and hosted on G2.com.

What I like most about SAS Viya is its cloud-native architecture and strong performance. It enables faster data processing through in-memory analytics, supports Python, R, and SQL alongside SAS, and offers convenient access via a web-based interface. Overall, these capabilities make analytics more scalable, collaborative, and flexible than in traditional SAS environments. Review collected by and hosted on G2.com.

What I dislike about SAS Viya is its steeper learning curve, particularly for users who are new to cloud environments. Migrating from SAS 9 can be complex, and the administration and licensing costs can be high. In addition, some traditional SAS features behave differently in Viya, which may require adaptation, retraining, and extra time to adjust. Review collected by and hosted on G2.com.

SAS Viya provides a unified, cloud‑native platform that combines advanced analytics and AI tools with strong flexibility for both coders and non‑technical users. It simplifies data preparation and visualization, integrates smoothly with existing systems, and supports tasks ranging from quick exploration to complex modeling. Its machine learning and governance features ensure enterprise‑level trust and transparency, while fostering accessibility and collaboration across teams. The onboarding process was seamless, and the supportive trainer enhanced the overall experience. Review collected by and hosted on G2.com.

While SAS Viya stands out as a robust analytics platform, it does come with a number of challenges. The cost can be a significant barrier for smaller teams, especially when compared to open-source options. The interface is generally user-friendly, but accessing and mastering advanced features often involves a steep learning curve, particularly for those new to SAS. Although integration with Python and R is available, it can feel unwieldy at times, and the platform's performance may fluctuate depending on the specific cloud environment. Additionally, the documentation sometimes lacks depth for more complex troubleshooting, which can make SAS Viya less suitable for organizations that prioritize flexibility and cost-effectiveness. Review collected by and hosted on G2.com.

What I like best about SAS Viya is its ability to combine powerful analytics with a modern, cloud-native architecture.

It provides a unified platform where data preparation, machine learning, reporting, and model deployment all happen in one place. The scalability is excellent because it runs on Kubernetes, which makes it easy to handle large workloads and integrate with existing cloud environments.

I also appreciate how user-friendly it is for both technical and non-technical users — from data scientists who prefer coding to business users who rely on visual interfaces. This combination of flexibility, performance, and ease of collaboration is what really stands out. Review collected by and hosted on G2.com.

While SAS Viya is a powerful analytics platform, there are a few areas that could be improved:

High learning curve: Some advanced features can feel complex for new users, especially those without prior SAS experience.

Cost and licensing model: Viya can be relatively expensive for organizations with limited budgets.

Resource consumption: The platform can be heavy on infrastructure resources, which requires strong hardware or cloud capacity.

User interface complexity: Although it has improved over time, some parts of the UI can still feel less intuitive compared to newer analytics tools.

Integration challenges: Integrating Viya with certain external systems or custom pipelines sometimes requires additional effort. Review collected by and hosted on G2.com.

I appreciated SAS Viya's straightforward approach in providing detailed keyword and sentiment analysis, as well as its ability to show correlations between keywords. I loved the term map and sentiment analysis features because they show correlations between all keywords and classify them which is very helpful. I also found the data it provided to be clear, making it easy to identify trends. Another feature I liked was the flexibility to use both visual and programming interfaces, particularly with R, allowing me to customize categories for analysis. Additionally, the initial setup was easy, and the examples provided were clear. Review collected by and hosted on G2.com.

It's just that there are some codes that require more rules and they are not specified in description pages. It would be nice if the examples could be expanded. Review collected by and hosted on G2.com.

I particularly like SAS Viya's cloud native architecture and scalability, enabling seamless integration of data preparation, advanced analytics, and machine learning within a single platform. The user-friendly UI combined with powerful statistical capabilities makes it efficient for both technical users and business stakeholders. I appreciate its strong governance, model management, and deployment capabilities, which make transitioning from development to production very smooth and reliable. Review collected by and hosted on G2.com.

I believe while SAS Viya is a very powerful analytics platform, there is still room for improvement in terms of ease of onboarding and cost structure. The learning curve can be steep for new users, especially when transitioning from open-source ecosystems like Python. Additionally, deeper integration and flexibility with certain third-party tools, and more streamlined UI workflows, could further enhance the product's usability. Also, expanding community resources and documentation would be helpful for smoother adoption for smaller teams. Review collected by and hosted on G2.com.

I use SAS Viya for my University assignments and personal projects, and it makes my work easier because of its ease of use and simplicity, which saves me a lot of time. I particularly like how I can connect different nodes to see final results, which helps a lot with analysis. Connecting nodes allows me to see final results and different values like precision and F1 scores. Also, the initial setup is super easy and hassle-free. Review collected by and hosted on G2.com.

I personally do not like how SAS Viya does not have a way of working with a team together. If I'm working with my team and I need to share some ideas or connect my ideas with my teammates, I feel it is not possible because there are no cloud sharing options. Review collected by and hosted on G2.com.

I love SAS Viya for its incredible accuracy in data management and its powerful data visualization capabilities. The platform excels in generating a variety of report visualizations with great accuracy and without latency. This accuracy ensures that human errors are minimized in our operations. Additionally, SAS Viya's capability to handle bulk data allows me to process and analyze large datasets quickly, even in real-time. The real-time dashboard features enable us to track operational metrics, monitor agent performance, and analyze call volumes effectively. These features are especially valuable in a call center context as they provide timely insights that enhance client satisfaction and operational efficiency. The ability to conduct accurate and fast analytics makes SAS Viya essential in maintaining high standards for the reports we deliver to our clients. Review collected by and hosted on G2.com.

I find some features of SAS Viya complex for new users. This complexity can be daunting and might require additional resources or time to become proficient. Also, processing large data sets feels slower than I would expect, which can hinder efficient analysis and timely decision-making. Review collected by and hosted on G2.com.

I like SAS Viya for its powerful analytics combined with a very intuitive interface, which lets me move seamlessly from data preparation to modeling to visualization all within the same environment, without having to constantly switch tools. This seamless transition keeps my workflow connected and reproducible, reducing errors and saving time as I don't need to export files or switch platforms. I also appreciate how it allows for efficient management and analysis of large datasets. The setup was relatively smooth because of its easy-to-navigate interface. Review collected by and hosted on G2.com.

One area that could be improved is flexibility compared to open-source tools. While SAS Viya is powerful, I sometimes feel it can be less customizable than environments like Python, especially when I want to implement very specific or cutting-edge methods. Review collected by and hosted on G2.com.