SAS Viya Reviews & Product Details

I have been using SAS Viya for data analysis for five years, and I appreciate its role in seamlessly transitioning from SAS Enterprise Miner during my mechanical engineering degree. I find it especially helpful for inventory management in my store, where it effectively addresses numerous data analysis challenges. Setting up SAS Viya was a breeze, largely due to its compatibility with virtual lab environments where most settings are pre-configured. The integration with SAS Studio, and the ability to use the PROC MIRP procedure, greatly facilitate my inventory management tasks. I find the data engineering tools particularly useful, with the 'data step' feature being my go-to tool for data engineering tasks. Its ability to pull data from my ERP system via SES, API tool, and perform data manipulations, as well as create basic graphs, is highly beneficial. Moreover, I have integrated Microsoft Excel with SAS Viya successfully, which enhances my workflow. I am particularly impressed with SAS Viya's integration capabilities with other applications like SAS Model Studio and SAS Visual Analytics, which make it an exceptionally versatile tool. Review collected by and hosted on G2.com.

I find the SAS Visual Analytics application a bit rigid and would appreciate more flexibility. Review collected by and hosted on G2.com.

What I like best about SAS Viya is its modern, cloud-native architecture built on Kubernetes, which makes it scalable, flexible, and easy to deploy across different environments. It provides a unified platform that integrates data management, analytics, AI, and visualization in one place, allowing users to move seamlessly from data preparation to model deployment. I also appreciate its multi-language support for SAS, Python, and R, enabling collaboration between different teams, along with its intuitive web-based tools like SAS Studio and Visual Analytics. Additionally, Viya offers strong governance, enterprise-grade security, and high-performance in-memory processing through CAS, making it both powerful and user-friendly for a wide range of analytics workloads. Review collected by and hosted on G2.com.

One aspect I find challenging about SAS Viya is its tendency to be resource-intensive, often demanding substantial CPU, memory, and storage to operate efficiently, particularly in larger environments. The process of installation and upgrading can also be quite complicated, as it typically involves coordinating multiple services and dependencies. Furthermore, troubleshooting can be a lengthy process, since it sometimes requires in-depth knowledge of both SAS components and the underlying infrastructure. I also think that some users might perceive the interface and integration with third-party tools as less intuitive when compared to more modern, lightweight analytics platforms. Review collected by and hosted on G2.com.

I really value having data preparation, management, analytics, and machine learning all gathered under one roof with SAS Viya. Before using it, I was spending a lot of time reconciling data across different environments. Now, the integrated workflow from data preparation through to model deployment in one environment has streamlined the process. I can trace any figure in a report back to its source, which is a huge help when preparing for internal reviews. Review collected by and hosted on G2.com.

The spatial and geostatistical procedures need refinement before I would trust them unvalidated for location-based modeling, and the documentation around those routines should be considerably more detailed than it currently is. Variogram fitting is sensitive to parameter choices, and the interpolated surfaces tend to smooth over genuine differences between adjacent submarkets when property data clusters unevenly. There's also a lack of diagnostics on fit and prediction uncertainty, which means I have to validate anything for a valuation or investment committee paper in a separate GIS tool. Review collected by and hosted on G2.com.

For coding, I really like the feature where SAS provides a preview of the code you’re about to write. For example, if I want to use the UPCASE function on a variable, as I’m typing it in SAS Studio, it shows a preview that helps me write the code faster and saves time. Review collected by and hosted on G2.com.

I struggle to see the full output data. I always have to scroll horizontally to view it, which makes it hard to read. It would be nice if there were a way to view all the output data and the code without needing a monitor, maybe by having separate tabs—one for output data, one for the log, and one for the code. Another thing is that I want to use SAS Viya copilot, but I don’t have access to it yet. If I’m not mistaken, it should come out later in November. Review collected by and hosted on G2.com.

I like how it simplifies integration, and the AI-powered analytics automatically surface key insights. It’s been a game-changer for our reporting experience. We’ve been able to create and refine reports without needing constant input from the engineering team, which has saved us countless hours and made the investment feel fully justified. Review collected by and hosted on G2.com.

They provide exceptional customer service. Their team is consistently responsive, knowledgeable, and proactive, and they’ve helped us get the most out of the platform and fully maximize its potential. Review collected by and hosted on G2.com.

For me, one of the biggest advantages has been its accessibility. I appreciated that, as soon as our data sources were connected, the platform immediately began organizing everything into interactive analyses without requiring any configuration on our part. It essentially handled the entire reporting workflow end to end, from building interactive dashboards and generating reports to surfacing key patterns. Review collected by and hosted on G2.com.

Our integration experience was exceptionally smooth, especially compared with more traditional business intelligence solutions. I honestly have nothing negative to say—the interface feels modern and intuitive, and it requires virtually no training to get started. Review collected by and hosted on G2.com.

What I find most helpful about SAS Viya is that it provides a modern, centralized analytics environment where users can access data, perform analysis, build models, and create visual reports. One of its biggest advantages is its ability to handle large datasets efficiently while providing both programming and user-friendly visual tools. Review collected by and hosted on G2.com.

The least helpful aspect of SAS Viya is that it can sometimes feel complex, especially when learning the platform for the first time. There are many tools, features, and interfaces to understand, which can make navigation and troubleshooting challenging. Review collected by and hosted on G2.com.

I appreciate how SAS Viya brings order to the data flowing in from our study sites, allowing me to clean, standardize, and reconcile it into a single, dependable source. The automation spares me much repetitive processing, and the audit trail and access controls keep everything aligned with our strict standards. What wins me over is the analytical muscle behind an approachable workspace, letting me consolidate and interrogate large volumes of data. The governance controls assure me that sensitive information stays exactly where it should, keeping our data defensible under strict regulatory standards. I also find the analytical capabilities valuable for profiling and validating large datasets quickly, surfacing anomalies early on. Additionally, I use it alongside Workato and Egnyte to ensure clean data flow and secure storage. Review collected by and hosted on G2.com.

The learning curve is steep, and the more advanced capabilities call for a fair investment in training before they yield their full value. The licensing and infrastructure requirements are considerable too, and would give a smaller outfit pause. These are the costs of a platform built for serious work rather than shortcomings in the tool itself. The initial setup was more involved than most, requiring support from our IT team to get the environment properly configured before I could begin working in it. Review collected by and hosted on G2.com.

An intelligent tool that can leverage large volumes of data from diverse sources, while adapting to different formats and structures. It provides flexibility, automation, scalability, monitoring and debugging, security, and regulatory compliance. It also features an excellent portal with tools for data orchestration, analysis, and automation. Review collected by and hosted on G2.com.

Like any technology, it may come with certain limitations or challenges. That said, at the moment I don’t have anything negative to say about it. I see it as an incredibly powerful tool for processing information and analyzing data. Review collected by and hosted on G2.com.

The Cloud Analytic Services (CAS) engine stands out because it processes data entirely in-memory across distributed nodes. Its architecture also multi-threads operations by default, which reduces the need for routine sorting before procedural steps and helps cut runtimes for massive clinical datasets. Another strength is language flexibility: you can write and run standard SAS code alongside open-source languages like Python and R within a single analytical pipeline. Finally, the unified, web-based environment brings SAS Studio programming together with visual analytics, so you don’t have to transfer files back and forth between separate desktop tools. Review collected by and hosted on G2.com.

The main drawbacks center around architectural overhead and migration friction. Steep infrastructure demands. Running the platform requires deep Kubernetes expertise and significant hardware resources. Cost. The combined expense of the software licensing and the continuous cloud compute required for the in-memory engine is high. Legacy code compatibility. Traditional SAS 9.4 code does not automatically benefit from the Cloud Analytic Services (CAS) engine. Scripts must be rewritten to handle distributed processing logic. Procedure limitations. Some specific analytical PROCs lack native CAS support. These must run on the traditional Compute Server, which negates the platform's speed advantages. Review collected by and hosted on G2.com.