SAS Viya

What SAS Viya is

SAS Viya is an analytics platform from SAS Institute, and its low-code/no-code side is the part this entry covers. Through SAS Visual Analytics, the data visualization software on the same platform, people build dashboards, reports and visual analyses by dragging and dropping, and they reach AI and machine learning through a visual interface. The company's site headline reads: "Everyone can access AI and machine learning in a visual, easy-to-use environment." The site points to a corporate headquarters in Cary, NC, USA.

It is written for two readers at once. Business analysts and other non-experts get trusted results without programming, and data scientists get a faster way to explore data before they build models. The company's site says that "anyone, including data scientists, can create dashboards and gather insights using a low-code/no-code interface." The Italian version of the page describes SAS Viya as a single cloud-ready environment available to everyone from data scientists to business analysts, developers and executives.

What you build and how

The editor is a single, self-service interface. The company says it lets you visually explore data as well as create and share "smart visualizations and interactive reports." The page is explicit about the skill bar: "No programming knowledge is needed. Simply drag and drop to discover powerful insights." Its argument is that data discovery is a long process that consumes critical time and resources for data scientists, and that even people who are not analytics experts need access to trusted results.

Dashboards and reports come from SAS Visual Analytics, which the page lists as a way to "Discover and explore relationships in data, and share insights." The Italian page describes it as the tool to explore your data visually, discover new business patterns and publish reports on the web and on mobile devices, with reporting and mobile BI. A webinar linked from the page, "How do I build a report in SAS Visual Analytics on SAS Viya?", is pitched as a demonstration of how quick and easy building a report is. Another, "Take Your SAS Visualizations to the Next Level," covers the extended visualization capabilities in SAS Viya for creating visualizations in a low-code/no-code environment and sharing them through different channels.

Data preparation happens in the same drag-and-drop style. The page says you can streamline discovery "by importing your own data, joining tables, applying data quality functions, creating calculated columns and more," and that you can "Access, profile, combine, clean and transform your data using an intuitive, self-service interface with embedded AI in a trusted, governable environment." For an analyst, that means the cleanup that usually happens in a separate tool sits next to the chart builder.

The analytics layer is where the machine learning membership sits. The page says augmented analytics and advanced capabilities accelerate insights and help uncover stories hidden in your data. Named capabilities include "Automated forecasting, goal seeking, scenario analysis, decision trees and more," available "regardless of your skill level." Automated explanations describe important results "in a natural language format that anyone can understand," so a report reader does not need to interpret a model's output alone.

Model building goes further than charts. Under the heading "Adopt a launchpad for analytics," the page says you can drag and drop to create "visually generated machine learning models that you can deploy without coding," autotune model hyperparameters "to improve accuracy in only two clicks," and export models into advanced machine learning pipelines "for ultimate control over models." That export step is the handoff from the no-code side to data scientists: a business analyst can build and tune a first model visually, and a specialist can take it into a full pipeline on the same platform.

An e-book promoted on the page, "Augmented Analytics: The secret ingredient to better business intelligence," is described as showing how AI and machine learning tools can assist with tasks across the entire analytics life cycle. The page also lists SAS Viya's benefits as faster data integration, effective model development and reduced cloud costs.

Governance has its own product. The page recommends SAS Data Governance, formerly SAS Information Governance, to "Democratize your data, enhance collaboration and facilitate regulatory compliance," alongside Visual Analytics and Viya. The key topics menu names the neighboring areas of the same product family: Overview, Low-Code/No-Code, Embedded Analytics, Automated Insights, Location Intelligence and Augmented Analytics for Data Scientists, which shows that embedding, automated insights and location analysis are part of the wider offer. The site's main menu also lists Managed Cloud Services and Generative AI Solutions.

Plans, support and training

The site publishes no prices or plan names. There is a "Try SAS Viya for Free" button at the top of the low-code page, and the site's account area offers access to My SAS, trials and communities.

Support resources are extensive. The menu lists documentation at documentation.sas.com, community forums at communities.sas.com, guides on installation and configuration, SAS Viya administration, SAS Viya programming and system requirements, and a worldwide contacts list for finding your region.

For training, a separate page describes SAS Skill Builder for Students, which gives academics free access to SAS software and training. It describes a browser-based programming environment where learners use coding or point-and-click tasks, a library of SAS e-learning courses with tutorials, videos and online communities, and certification exam prep with practice exams and badges for a CV. The main menu also lists free practice exams and credentials.

The footer describes SAS data and AI solutions as providing "global customers with knowledge they can trust in the moments that matter."

Who it suits and who it does not

SAS Viya suits organizations where analysts of different skill levels share one analytics environment. A finance or operations analyst can prepare data and build dashboards without a programmer, while a data scientist uses the same visual tooling for exploration, then exports models into pipelines. The named features, automated forecasting, goal seeking and scenario analysis, fit teams that want projections without building a statistical workflow first, and the governance product fits a regulated company.

It also suits teams that value training and certification, since the vendor runs a free student program and a library of e-learning.

The caveat is scope. This is an enterprise platform with several products around it, not a quick personal tool, and with no published pricing a founder or a small team cannot judge cost from the site. A solo builder who wants a polished dashboard this afternoon will find lighter tools; a company with data scientists and analysts under one roof is the audience.