SAS Institute Inc. is an American software company specializing in the use of data. Based in Cary, North Carolina, the company provides tools to prepare information, build statistical models and inform operational decisions. Its offerings are aimed in particular at banks, insurers, manufacturers, healthcare organizations and public bodies. Its website is sas.com.
From academic roots to software development
The history of SAS begins in the 1960s with an academic statistical analysis project, developed notably at North Carolina State University to work with agricultural data. The name SAS comes from “Statistical Analysis System.” The company was established in 1976, with Jim Goodnight and John Sall among its founders, to commercialize and develop these tools.
Over the decades, the software company expanded its scope: data management, decision support, forecasting and machine learning joined statistics. The SAS language and its associated procedures became firmly established in organizations that need reproducible, documented processing integrated into their business processes, particularly in regulated environments.
Turning data into decisions
SAS’s activities cover much of the analytics workflow: access to sources, data preparation and quality, visual exploration, modeling, followed by model deployment and monitoring. Its SAS Viya platform brings together analytics and artificial intelligence capabilities in an architecture designed for cloud environments. It also supports working with languages such as Python and R alongside the company’s established technologies.
SAS applies these capabilities in industry-specific solutions. In finance, its software is used in particular for risk management, fraud detection and anti-money laundering. In manufacturing and retail, it can help forecast demand or optimize operations. Healthcare and clinical research are also major areas of use for its statistical tools.
Its business model is based on the sale of software and related services, including consulting, support and training. Industry knowledge and continuity of existing processing play an important role in its relationships with customers.
What next?
For SAS, the challenge is to modernize this legacy without forcing disruption on the organizations using its products. The development of Viya responds to demand for scalable processing, integration with cloud infrastructure and collaboration among statisticians, developers and business teams.
Faced with cloud data platforms and open-source ecosystems, the software company must demonstrate the value of its integrated tools. Governance, explainability and model monitoring are areas of differentiation as artificial intelligence becomes part of more sensitive processes. Its trajectory will also depend on its ability to simplify migrations and keep operating costs under control for its customers.