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A work-in-progress of a SAS (software) Wiki that is more complete, accurate, heavily verified and neutral in tone. Prior negative opinions were not removed, but better balanced and verified. If you feel any of these changes introduce bias or are not an improvement to the Wiki, or have other suggestions, please visit my Talk page using Assume Good Faith.

Analytics447 (talk)

This page is about SAS the product. For the company, see SAS Institute. For the language, see SAS language.
SAS
Developer(s)SAS Institute
Stable release
9.3 / July 12, 2011
Written inC
Operating systemWindows, IBM mainframe, Unix/Linux, OpenVMS Alpha
Typenumerical analysis
Licenseproprietary
Websitewww.sas.com

SAS is an analytics software suite of over 200 products developed by SAS Institute.[1] SAS draws from statistics, machine learning, laboratory analysis, computational science, operations research, graph theory, measurement science and natural language processing disciplines to predict, measure, analyze and decide based on data. Use case scenarios span dozens of industries and applications, including fraud, risk, compliance, performance management, customer/marketing analysis and supply chain management.[2]

A SAS application may combine data integration, data quality, data mastering, enterprise data access and data governance to source, cleanse and pool operationally generated and third party data into an accurate source of input for analytical modeling. Analysis engines then apply a series of transformations, models and testing routines relevant to the use case. Analysis results are delivered to operational systems, dashboards, reports and other graphical user interfaces where they are consolidated, presented and used for automated or business-level decisions.[2]

SAS utilizes grid and in-database computing algorithms and methods to address extremely large data volumes.[3]

History

SAS' Beginnings in Academics

SAS was conceived by Anthony J. Barr in 1966.[4] As a North Carolina State University graduate student from 1962 to 1964, Barr created an analysis of variance (ANOVA) modeling language inspired by statistician Maurice Kendall and a multiple regression program that generated machine code for performing algebraic transformations of raw data. Drawing on those programs and his experience with structured data files,[5] Barr created the Statistical Analysis Software (SAS) that were the beginnings of the SAS product set. From 1966 to 1968, Barr developed the fundamental structure and language of SAS.

In January 1968, Barr and James Goodnight integrated new multiple regression and analysis of variance routines developed by Goodnight into Barr's framework.[6][7]

In 1973, John Sall joined the project, making extensive programming contributions in econometrics, time series, and matrix algebra. Other participants in the early years included Caroll G. Perkins, Jolayne W. Service, and Jane T. Helwig. Perkins. Service and Helwig created the early documentation.[6] In 1976, SAS Institute, Inc. was incorporated by Barr, Goodnight, Sall, and Helwig.

The First SAS Products

SAS 71 was released in 1971 as the very first limited release of SAS.[8] SAS 72, released the following year was more well-rounded and added features for handling missing data and combining data sets.[9][10][11]

In 1976, SAS was rebuilt from scratch in SAS 76 with an open architecture that allowed compilers and procedures. It also was able to use any data format on an IBM mainframe, generate reports and handle general linear models.[11][12][13][14] At the time SAS was used by just 100 customers and a single SAS program consisted of 150 boxes of paper cards.[15] In 1979, SAS/Graph and SAS/ETS products added graphing, econometric and time-series analysis capabilities and were some of the first products added to Base SAS.

SAS Version 5 was released in 1983. It was the first SAS release for the minicomputer. In 1986, SAS Version 6 presented a major milestone. The backend of the software was re-written in C. This made SAS available on UNIX, MS-DOS and Windows and opened up the system to C programmers. It also changed the physical format of SAS databases on the mainframe version so it could be copied from any media. These updates in the ‘80s shifted SAS from something that was only accessible with large mainframe computers, to something any computer user could use.

A Maturing Technology

From 1987 to 1999 SAS released a large number of products that supplement Base SAS for different use cases and add features.

  • 1987 – 1990: SAS introduced SAS/QC, SAS/IML, SAS/STAT, SAS/ASSIST and SAS/CPE. SAS/SHARE introduced concurrent updates to SAS data sets. MultiVendor Architectures was a landmark improvement that allows BASE SAS to run on every major operating system and access any common data source.[16]
  • 1991 - 1995: SAS introduced SAS/INSIGHT for data visualization, SAS/CALC, SAS/TOOLKIT, SAS/PH-Clinical, SAS/LAB, ODBC, SAS/SPECTRAVIEW, SAS/SHARE .NET products and a data step debugger as well as Web enablement of SAS software.
  • 1996 - 1999: SAS introduced SAS/Warehouse Administrator, SAS/IntrNet, Balanced Scorecard, SAS/Enterprise Reporter, SAS HR Vision, as well as CRM products, Risk Dimension software and an ERP interface for SAS/ACCESS. SAS Version 7 debuted with a new Output Delivery System and improved text editor. In 1999, SAS Version 8 was released. SAS Enterprise Miner was first introduced, which allowed users to quickly extract information or insights from large data sets, opening up new applications for analytics.

    • Modern Era

    In 2004 SAS released Version 9.0, which was dubbed “Project Mercury” and designed to make SAS accessible by a broader range of business users.[17][1] Version 9.0 includes custom user interfaces based on the user’s role and the ability to deal with larger data volumes. With version 9, the SAS Enterprise Guide played a more prominent role as the user interface of SAS. SAS Enterprise guide is a point-and-click interface with wizards that allow researchers or analysts to drag and drop data sets, actions and analyses.[17][18]

    SAS Interaction management was also introduced in 2004 as an enhancement to CRM capabilities.[19] In 2008 SAS announced Project Unity, a project to integrate data quality, data integration and master data management.[20]

    Latest Updates

    In 2010 SAS Social Media Analytics was released, a tool for social media monitoring, engagement and sentiment analysis.[27, 94] That same year the SAS Rapid Predictive Modeler (RPM) was released to allow less sophisticated users to create basic analytical models in Microsoft Excel.[21][22]

    Technical Description

    In progress

    Use Cases

    Customer Intelligence

    Many SAS products are used to plan, optimize and execute marketing strategy and customer interaction through workflow, reporting and analytics. SAS often predicts what a customer is most likely to have an interest in buying based on customer data. It develops propensity scores and other measures that are used within marketing campaigns to do segmentation, targeting and to determine content relevance in phone, Web and E-mail communications with prospects. Predictive analytics are also used to prioritize marketing efforts given time, resource and other constraints. SAS products may also resolve customer feedback, prior sales performance and other data to predict, analyze, and optimize the success of a product.[23] Other products collect internal, mobile, Web and social data to create customer profiles. The strategy and planning tools create models and reports that match marketing plans to corporate priorities and resource constraints. Workflow and automation tools support the management of marketing campaigns and customer interactions across channels.[24][25]

    Fraud and Financial Crimes

    SAS analyzes financial transaction data as the transactions take place to identify suspicious activity and support related processes. The system can block transactions before they’re processed to prevent losses from suspected fraud. It assists fraud investigators by mapping out the growth of suspected organized fraud networks, and evaluating the likelihood of fraud through a case management system. Some applications use advanced analytics and account data, while others like the Case Management product are focused on process activity.[26][27]

    Governance, Risk and Compliance (GRC)

    SAS Enterprise GRC applications have products for auditing, compliance, policy and risk that are often combined with other products for finances, supply chain, visualization, activity management or others. Each involves events like a financial loss on the stock market or a suspected misrepresentation of financial information. These events trigger an issue and associated action plans, documents, requirements and compliance needs are identified. Then the user is guided through remediation of the issue in order to keep promises, properly audit, maintain compliance or mitigate risk.[28][29][29]

    IT Resource Management

    SAS IT management applications analyze IT resource utilization and performance data about IT assets like IT assets like servers, storage devices, networks and applications. The application generates reports, analysis, and metrics on IT resource availability and forecasted demand so organizations can plan IT infrastructure resources. It can also examine performance in relation to costs.[30][31]

    Performance Management

    In progress

    Risk Management

    SAS risk management applications support the management of economic and regulatory risk related to investments, credit, liability and corporate operations. These applications incorporate data integration, analytics and reporting to understand and assess the risks associated with specific choices and the likelihood of potential outcomes. For example, there are SAS applications specifically for evaluating the likelihood of credit losses, the chances an insurance quote applicant will have future claims or calculating the regulatory capital requirements to meet Pillar 1 of the Basel 2 regulations.[32][33]

    Supply Chain Intelligence

    In progress

    Sustainability Management

    SAS has two products that present and analyze sustainability performance using globally accepted sustainability KPIs. They measure and report on things like energy consumption, carbon footprint and other environmental and social factors. SAS models organizational emissions based on international carbon accounting standards and can evaluate the impact of alternative scenarios on corporate performance.[34][35]

    Market Share & Reception

    Analytics

    SAS held a 35.2 percent market share for advanced analytics as of 2010, more than twice that of the second largest share owner.[36][37] SAS’ traditional strengths are bringing traditional and advanced analytics closer together.[38]

    SAS is best known for its role in predictive analytics.[39] SAS’s predictive analytics and data mining were evaluated by Forrester against 53 criteria in three categories. SAS earned top overall ranking in all three categories, including perfect scores for functionality, professional services, licensing and cost, direction, and company financials.[40][41]

    Business Intelligence

    SAS is number three in terms of worldwide market share by revenue in the Business Intelligence(BI) market.[42][43] The company had 11 percent of the BI market as of 2010.[44]

    SAS Institute has grown mostly organically, with fewer acquisitions than other larger software vendors. As a result, its BI products are better integrated and SAS can almost fully concentrate on innovation rather than integration.[38]

    Data Management

    SAS Data Management includes data integration, data quality, master data management and enterprise data access products.[45] A 124-point review by Forrester found that DataFlux (a SAS subsidiary) stood out for their ability to generate customer loyalty through product ease of use, managing pricing complexity, effectively meeting and exceeding customer expectations, and delivering a positive account management experience.[46] SAS is in the Visionaries Quadrant for the Gartner 2010 Data Integration Tools Magic Quadrant.[47]

    Criticisms

    In Progress

    Features

    In Progress

    See Also

    References

    1. ^ a b By Rick Whiting, InformationWeek. “SAS Extends Business Intelligence to the Masses.” March 31, 2004.
    2. ^ a b SAS Website
    3. ^ By James Taylor, JT on EDM. “First Look – SAS High Performance Computing.” March 7, 2011.
    4. ^ Greenberg & Cox, et al. 1978:181. Reference to the creation of SAS by Barr in 1966.
    5. ^ Barr contributed to the development of the NIPS Formatted File System while working for IBM at the Pentagon from 1964 - 1966. FFS was one of the first data management systems to take advantage of files with a defined structure for efficiencies in data storage and retrieval.
    6. ^ a b (Barr & Goodnight, et al. 1976:"The SAS Staff") Attribution of contributions to SAS 72 and SAS 76 to Barr, Goodnight, Service, Perkins, and Helwig.
    7. ^ (Barr & Goodnight et al. 1979:front matter) Attribution of the development of various parts of the system to Barr, Goodnight, and Sall.
    8. ^ (Barr & Goodnight 1971)
    9. ^ (Service 1972)
    10. ^ (Service 1972:47-49)
    11. ^ a b (Service 1972:28,65,67,etc.)
    12. ^ (Barr & Goodnight, et al. 1976:11-15)
    13. ^ (Barr & Goodnight, et al. 1976:38-44)
    14. ^ Barr & Goodnight, et al. 1976:127-144)
    15. ^ Company History | SAS
    16. ^ Base SAS Product Fact Sheet
    17. ^ a b By Dave Steven, The Pennsylvania State University. “SAS is Starting to Look Even Better....” July 29, 2002.
    18. ^ By Stephen McDaniel, Freakalytics. “The Joy of SAS Enterprise Guide.” September 26, 2007.
    19. ^ By Dennis Callaghan, eWeek. “SAS to Add to Analytical CRM Arsenal.” September 26, 2002.
    20. ^ By Antone Gonsalves, InformationWeek. “SAS, DataFlux Unveil 'Project Unity'.” October 10, 2008.
    21. ^ By Cindi Howson, InformationWeek. “SAS Takes Predictive Analytics Mainstream.” September 7, 2010.
    22. ^ UCLA Academic Technology Services. “Statistical Computing Seminars: Introduction to SAS Macro Language.”
    23. ^ James Taylor, JT on EDM. “First Look – SAS Customer Intelligence.” January 4, 2011.
    24. ^ YouTube. “SAS Customer Intelligence in Action”. April 1, 2009.
    25. ^ SAS Customer Intelligence Product Page.
    26. ^ YouTube. “SAS Fraud and Financial Crimes Solutions.” April 5, 2011.
    27. ^ Enterprise Fraud and Financial Crime Product Page
    28. ^ SAS Enterprise GRC Product Page
    29. ^ a b By Maria Bruno-Britz, Bank Systems and Technology. “SAS Unveils Fraud Case Management Module.” October 28, 2009. Cite error: The named reference "seventyeight" was defined multiple times with different content (see the help page).
    30. ^ IT Resource Management Product Page
    31. ^ IT Management News. “SAS Launches Suite of Solutions for IT.” September 22, 2004.
    32. ^ [http://www.sas.com/solutions/riskmgmt/ Risk Management Product Page
    33. ^ By Douglas Blakey, Retail Banker International. “SAS Ramps up its Risk Management Solution.” June 15, 2011
    34. ^ SAS Sustainability Product Page
    35. ^ Diplomacy Matters. “Sustainability Management at SAS.” November 18, 2010.
    36. ^ CIOL. “SAS Playing Strong in Advanced Analytics: IDC.” June 27, 2010.
    37. ^ Press Release. “SAS leads advanced analytics market by wide margin.” June 13, 2011.
    38. ^ a b By Boris Evelson, Forrester. “The Forrester Wave: Enterprise Business Intelligence Platforms, Q4 2010.” October 20, 2010. Retrieved August 30th, 2011.
    39. ^ 180 Systems SAS Review. October 2006.
    40. ^ By James Kobielus, Forrester. “The Forrester Wave: Predictive Analytics and Data Mining Solutions, Q1 2010.” February 4, 2010
    41. ^ Press Release. “Independent research firm recognizes SAS as a leader in predictive analytics, data mining.” February 5, 2010.
    42. ^ News Page. “SAS No. 2 in BI Market Worldwide.”
    43. ^ By Dan Vesset, IDC. “Worldwide Business Intelligence Tools 2010 Vendor Shares.” June, 2011. Retrieved September 13, 2011.
    44. ^ By Dan Vesset, IDC. “Worldwide Business Intelligence Tools 2010 Vendor Shares.“ Retrieved August 30th, 2011.
    45. ^ SAS Data Management Site.
    46. ^ By Rob Karel, Forrester. “The Forrester Wave: Enterprise Data Quality Platforms, Q4 2010.” October 29, 2010. Retrieved August 30th, 2011.
    47. ^ Press Release. “SAS and DataFlux in Visionaries Quadrant for 2010 Data Integration Tools Magic Quadrant.” November 23, 2010.
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