SAS is a software suite that can mine, alter, manage and retrieve data from a variety of sources and perform statistical analysis on it.

[8] SAS data can be published in HTML, PDF, Excel, RTF and other formats using the Output Delivery System, which was first introduced in 2007.

[19] Barr was joined by student James Goodnight, who developed the software's statistical routines, and the two became project leaders.

[16][23] John Sall joined the project in 1973 and contributed to the software's econometrics, time series, and matrix algebra.

[3][25] It was used only on IBM mainframes and had the main elements of SAS programming, such as the DATA step and the most common procedures, i.e.

The ability to analyze general linear models was also added[29] as was the FORMAT procedure, which allowed developers to customize the appearance of data.

Version 5 introduced a complete macro language, array subscripts, and a full-screen interactive user interface called Display Manager.

[34][35][36][37] In January 2022, JMP became a wholly owned subsidiary of SAS Institute, having previously been a business unit of the company.

[38] SAS 6 was used throughout the 1990s and was available on a wider range of operating systems, including Macintosh, OS/2, Silicon Graphics, and PRIMOS.

[52][53] The following year, a High Performance Computing platform was made available in a partnership with Teradata and EMC Greenplum.

[58] The company has invested in the development of artificial general intelligence, or "strong AI", with the goal of advancing deep learning and natural language processing to the point of achieving cognitive computing.

[60] It announced an additional $1 billion investment into these areas in 2023, particularly for industries such as finance, insurance, government, health care and energy.

[61] In September 2023, the company announced its expansion of research into the applications of generative AI in analytics, data management and modeling.

Numerous SAS modules for web, social media and marketing analytics may be used to profile customers and prospects, predict their behaviors and manage and optimize communications.

The framework's primary functionality is to monitor transactions across different applications, networks and partners and use analytics to identify anomalies that are indicative of fraud.

There is also a SAS Enterprise Risk Management product-set designed primarily for banks and financial services organizations.

[76] There is also a "SAS for Sustainability Management" set of software to forecast environmental, social and economic effects and identify causal relationships between operations and their impact on the environment or ecosystem.

[79] SAS has products for specific industries, such as government, retail, telecommunications, aerospace, marketing optimization, and high-performance computing.

[83] In a 2005 article for the Journal of Marriage and Family comparing statistical packages from SAS and its competitors Stata and SPSS, Alan C. Acock wrote that SAS programs provide "extraordinary range of data analysis and data management tasks," but were difficult to learn and use.

[85] Competitors such as Revolution Analytics and Alpine Data Labs advertise their products as considerably cheaper than SAS's.

Viya also increased interoperability with open source software, allowing models to be built in tools such as R, Python and Jupyter, and then executed on SAS's Cloud Analytics Services (CAS) engine.

[99] SAS has been named in the Gartner Leader's Quadrant for Data Integration Tools and for Business Intelligence and Analytical Platforms.

[105][106][107] SAS' analytical software is widely used in the petroleum and natural gas industry as well as global manufacturing.

[108][109] SAS and the International Institute for Applied Systems Analysis launched an app that crowdsources image data related to deforestation to train AI algorithms that  can identify human impact on the environment.

[112] SAS' risk management and fraud prevention software are widely used by governmental organizations and private enterprises.

[115] SAS develops data analysis and machine learning techniques that are widely applied in healthcare, medical research and life sciences.

[116] SAS has partnered on public health initiatives with the Centers for Disease Control and Prevention and Black Dog Institute.

[118] During the COVID-19 pandemic, the clinic used predictive models developed by SAS to forecast factors such as patient volume, availability of medical equipment and bed capacity in various scenarios.

SAS joined UNC Chapel Hill's Rapidly Emerging Antiviral Drug Development Initiative (READDI) in 2021.

[119] In 2023, the Texas state government contracted SAS to build a centralized visualization platform for predicting and tracking future outbreaks of influenza.