SAS (software)

SAS (previously "Statistical Analysis System")[1] is a statistical software suite developed by SAS Institute for data management, advanced analytics, multivariate analysis, business intelligence, criminal investigation,[2] and predictive analytics.

This article is about the software suite. For other uses, see SAS (disambiguation).
SAS
SAS 9 on Microsoft Windows
Developer(s)SAS Institute
Initial release1976 (1976)
Stable release
9.4M7 / August 18, 2020 (2020-08-18)
Written inC
Operating systemWindows, IBM mainframe, Unix/Linux, OpenVMS Alpha
TypeNumerical analysis
LicenseProprietary
Websitewww.sas.com/en_us/home.html

SAS was developed at North Carolina State University from 1966 until 1976, when SAS Institute was incorporated. SAS was further in the 1980s and 1990s with the addition of new statistical procedures, additional components and the introduction of JMP. A point-and-click interface was added in version 9 in 2004. A social media analytics product was added in 2010.

Technical overview and terminology

SAS is a software suite that can mine, alter, manage and retrieve data from a variety of sources and perform statistical analysis on it.[3] SAS provides a graphical point-and-click user interface for non-technical users and more through the SAS language.[3]

SAS programs have DATA steps, which retrieve and manipulate data, and PROC steps, which analyze the data.[4] Each step consists of a series of statements.[5]

The DATA step has executable statements that result in the software taking an action, and declarative statements that provide instructions to read a data set or alter the data's appearance.[4] The DATA step has two phases: compilation and execution. In the compilation phase, declarative statements are processed and syntax errors are identified. Afterwards, the execution phase processes each executable statement sequentially.[6] Data sets are organized into tables with rows called "observations" and columns called "variables". Additionally, each piece of data has a descriptor and a value.[4][7]

The PROC step consists of PROC statements that call upon named procedures. Procedures perform analysis and reporting on data sets to produce statistics, analyses, and graphics. There are more than 300 named procedures and each one contains a substantial body of programming and statistical work.[4] PROC statements can also display results, sort data or perform other operations.[5]

SAS macros are pieces of code or variables that are coded once and referenced to perform repetitive tasks.[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.[9] The SAS Enterprise Guide is SAS's point-and-click interface. It generates code to manipulate data or perform analysis automatically and does not require SAS programming experience to use.[10]

The SAS software suite has more than 200[11] components[12][13] Some of the SAS components include:[3][12][14]

  • Base SAS – Basic procedures and data management
  • SAS/STAT – Statistical analysis
  • SAS/GRAPH – Graphics and presentation
  • SAS/OR – Operations research
  • SAS/ETS – Econometrics and Time Series Analysis
  • SAS/IML – Interactive matrix language
  • SAS/AF – Applications facility
  • SAS/QC – Quality control
  • SAS/INSIGHT – Data mining
  • SAS/PH – Clinical trial analysis
  • Enterprise Miner – data mining
  • Enterprise Guide - GUI based code editor & project manager
  • SAS EBI - Suite of Business Intelligence Applications
  • SAS Grid Manager - Manager of SAS grid computing environment

History

Origins

The development of SAS began in 1966 after North Carolina State University re-hired Anthony Barr[15] to program his analysis of variance and regression software so that it would run on IBM System/360 computers.[16] The project was funded by the National Institutes of Health.[17] and was originally intended to analyze agricultural data[12][18] to improve crop yields.[19] Barr was joined by student James Goodnight, who developed the software's statistical routines, and the two became project leaders.[15][16][20] In 1968, Barr and Goodnight integrated new multiple regression and analysis of variance routines.[21][22] In 1972, after issuing the first release of SAS, the project lost its funding.[17] According to Goodnight, this was because NIH only wanted to fund projects with medical applications.[23] Goodnight continued teaching at the university for a salary of $1 and access to mainframe computers for use with the project,[17] until it was funded by the University Statisticians of the Southern Experiment Stations the following year.[16][23] John Sall joined the project in 1973 and contributed to the software's econometrics, time series, and matrix algebra. Another early participant, Caroll G. Perkins, contributed to SAS' early programming. Jolayne W. Service and Jane T. Helwig created SAS' first documentation.[21]

The first versions of SAS were named after the year in which they were released.[24] In 1971, SAS 71 was published as a limited release.[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 in the PROC step.[24] The following year a full version was released as SAS 72, which introduced the MERGE statement and added features for handling missing data or combining data sets.[26] In 1976, Barr, Goodnight, Sall, and Helwig removed the project from North Carolina State and incorporated it into SAS Institute, Inc.[27]

Development

SAS was re-designed in SAS 76 with an open architecture that allowed for compilers and procedures. The INPUT and INFILE statements were improved so they could read most data formats used by IBM mainframes. Generating reports was also added through the PUT and FILE statements. The ability to analyze general linear models was also added[28] as was the FORMAT procedure, which allowed developers to customize the appearance of data.[24] In 1979, SAS 79 added support for the CMS operating system and introduced the DATASETS procedure. Three years later, SAS 82 introduced an early macro language and the APPEND procedure.[24]

SAS version 4 had limited features, but made SAS more accessible. Version 5 introduced a complete macro language, array subscripts, and a full-screen interactive user interface called Display Manager.[24] In 1985, SAS was rewritten in the C programming language. This allowed for the SAS' Multivendor Architecture that allows the software to run on UNIX, MS-DOS, and Windows. It was previously written in PL/I, Fortran, and assembly language.[20][24]

In the 1980s and 1990s, SAS released a number of components to complement Base SAS. SAS/GRAPH, which produces graphics, was released in 1980, as well as the SAS/ETS component, which supports econometric and time series analysis. A component intended for pharmaceutical users, SAS/PH-Clinical, was released in the 1990s. The Food and Drug Administration standardized on SAS/PH-Clinical for new drug applications in 2002.[20] Vertical products like SAS Financial Management and SAS Human Capital Management (then called CFO Vision and HR Vision respectively) were also introduced.[29] JMP was developed by SAS co-founder John Sall and a team of developers to take advantage of the graphical user interface introduced in the 1984 Apple Macintosh[30] and shipped for the first time in 1989.[30] Updated versions of JMP were released continuously after 2002 with the most recent release being from 2016.[31][32][33][34][35][36][37]

SAS version 6 was used throughout the 1990s and was available on a wider range of operating systems, including Macintosh, OS/2, Silicon Graphics, and PRIMOS. SAS introduced new features through dot-releases. From 6.06 to 6.09, a user interface based on the windows paradigm was introduced and support for SQL [38] was added.[24] Version 7 introduced the Output Delivery System (ODS) and an improved text editor. ODS was improved upon in successive releases. For example, more output options were added in version 8. The number of operating systems that were supported was reduced to UNIX, Windows and z/OS, and Linux was added.[24][39] SAS version 8 and SAS Enterprise Miner were released in 1999.[20]

Recent history

In 2002, the Text Miner software was introduced. Text Miner analyzes text data like emails for patterns in Business Intelligence applications.[40] In 2004, SAS Version 9.0 was released, which was dubbed "Project Mercury" and was designed to make SAS accessible to a broader range of business users.[41][42] Version 9.0 added custom user interfaces based on the user's role and established the point-and-click user interface of SAS Enterprise Guide as the software's primary graphical user interface (GUI).[41] The Customer Relationship Management (CRM) features were improved in 2004 with SAS Interaction Management.[43] In 2008 SAS announced Project Unity, designed to integrate data quality, data integration and master data management.[44]

SAS Institute Inc v World Programming Ltd was a lawsuit with developers of a competing implementation, World Programming System, alleging that they had infringed SAS's copyright in part by implementing the same functionality. This case was referred from the United Kingdom's High Court of Justice to the European Court of Justice on 11 August 2010.[45] In May 2012, the European Court of Justice ruled in favor of World Programming, finding that "the functionality of a computer program and the programming language cannot be protected by copyright."[46]

A free version was introduced for students in 2010.[47] SAS Social Media Analytics, a tool for social media monitoring, engagement and sentiment analysis, was also released that year.[48][49] SAS Rapid Predictive Modeler (RPM), which creates basic analytical models using Microsoft Excel, was introduced that same year.[49][50] JMP 9 in 2010 added a new interface for using the R programming language from JMP and an add-in for Excel.[51][52] The following year, a High Performance Computing appliance was made available in a partnership with Teradata and EMC Greenplum.[53][54] In 2011, the company released Enterprise Miner 7.1.[55] The company introduced 27 data management products from October 2013 to October 2014 and updates to 160 others.[56] At the 2015 SAS Global Forum, it announced several new products that were specialized for different industries, as well as new training software.[57]

Releases date

SAS had many releases since 1972.[58] Since release 9.3, SAS/STAT has its own release numbering.

Release Date Comment
72 January 1972
76 July 1976
79.5 April 1981
82.4 January 1983
4.06 March 1984
5.03 July 1986
6.01 January 1985 PC DOS
6.03 March 1988
6.06 March 1990
6.07 April 1991
6.08 March 1993
6.09 October 1993
6.10 October 1994
6.11 October 1995
6.12 November 1996
7.0 October 1998
8.0 November 1999
8.1 July 2000
8.2 March 2001
9.0 October 2002
9.1 December 2003
9.1.3 August 2004
9.2 March 2008 STAT 9.2
9.2M2 April 2010 STAT 9.22
9.3 July 2011 STAT 9.3
9.3M2 August 2012 STAT 12.1
9.4 July 2013 STAT 12.3
9.4M1 December 2013 STAT 13.1
9.4M2 August 2014 STAT 13.2
9.4M3 July 2015 STAT 14.1
9.4M4 November 2016 STAT 14.2
9.4M5 September 2017 STAT 14.3
9.4M6 November 2018 STAT 15.1
9.4M7 August 2020 STAT 15.2

Software products

As of 2011 SAS's largest set of products is its line for customer intelligence. 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.[37][59] SAS also provides the SAS Fraud Framework. 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.[60][61][62][63] SAS Enterprise GRC (Governance, Risk and Compliance) provides risk modeling, scenario analysis and other functions[64][65] in order to manage and visualize risk, compliance and corporate policies. There is also a SAS Enterprise Risk Management product-set designed primarily for banks and financial services organizations.[66]

SAS' products for monitoring and managing the operations of IT systems are collectively referred to as SAS IT Management Solutions.[67] SAS collects data from various IT assets on performance and utilization, then creates reports and analyses.[68] SAS' Performance Management products consolidate and provide graphical displays for key performance indicators (KPIs) at the employee, department and organizational level.[69][70] The SAS Supply Chain Intelligence product suite is offered for supply chain needs, such as forecasting product demand, managing distribution and inventory and optimizing pricing.[71] 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 an impact on the environment or ecosystem.[72]

SAS has product sets for specific industries, such as government, retail, telecommunications and aerospace and for marketing optimization or high-performance computing.[73]

Free University Edition

SAS also offers Free University Edition which can be downloaded by anyone for non commercial use. The first announcement regarding this Free University Edition seems to have appeared in newspapers on 28 May 2014.[74]

Comparison to other products
See also: Comparison of statistical packages

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 use and learn.[75] SPSS and Stata, meanwhile, were both easier to learn (with better documentation) but had less capable analytic abilities, though these could be expanded with paid (in SPSS) or free (in Stata) add-ons. Acock concluded that SAS was best for power users, while occasional users would benefit most from SPSS and Stata.[75] A comparison by the University of California, Los Angeles, gave similar results.[76]

Competitors such as Revolution Analytics and Alpine Data Labs advertise their products as considerably cheaper than SAS'. In a 2011 comparison, Doug Henschen of InformationWeek found that start-up fees for the three are similar, though he admitted that the starting fees were not necessarily the best basis for comparison.[77] SAS' business model is not weighted as heavily on initial fees for its programs, instead focusing on revenue from annual subscription fees.[78][79]

Adoption

According to IDC, SAS is the largest market-share holder in "advanced analytics" with 35.4 percent of the market as of 2013.[80] It is the fifth largest market-share holder for business intelligence (BI) software with a 6.9% share[81] and the largest independent vendor. It competes in the BI market against conglomerates, such as SAP BusinessObjects, IBM Cognos, SPSS Modeler, Oracle Hyperion, and Microsoft Power BI.[82] SAS has been named in the Gartner Leader's Quadrant for Data Integration Tool and for Business Intelligence and Analytical Platforms.[83] A study published in 2011 in BMC Health Services Research found that SAS was used in 42.6 percent of data analyses in health service research, based on a sample of 1,139 articles drawn from three journals.[84]

See also

References
  1. "About SAS". Retrieved 5 July 2017.
  2. SAS empowers crime fighters to crack complex cases
  3. Salkind, Neil (2010). Encyclopedia of Research Design Encyclopedia of research design. doi:10.4135/9781412961288. ISBN 9781412961271.
  4. SAS Institute Inc. and World Programming Limited (England and Wales High Court (Chancery Division) July 23, 2010).Text
  5. Lora D. Delwiche; Susan J. Slaughter (2012). The Little SAS Book: A Primer : a Programming Approach. SAS Institute. p. 6. ISBN 978-1-61290-400-9.
  6. Arthur Li (10 April 2013). Handbook of SAS DATA Step Programming. CRC Press. p. 149. ISBN 978-1-4665-5238-8.
  7. Buck, Debbie. "A Hands-On Introduction to SAS DATA Step Programming" (PDF). SUGI 30: SAS Institute. Retrieved October 2, 2013.CS1 maint: location (link)
  8. N. Jyoti Bass; K. Madhavi Lata & Kogent Solutions (1 September 2007). Base Sas Programming Black Book, 2007 Ed. Dreamtech Press. pp. 365–. ISBN 978-81-7722-769-7.
  9. Tolbert, William (December 1, 2010). "How to Win Friends and Influence People with the SAS Output Delivery System". Clinical Medicine & Research. 8 (3–4): 189–190. doi:10.3121/cmr.2010.943.c-c1-04. PMC 3006529.
  10. Der, G.; B. S. Everittt (March 10, 2009). "Basic Statistics using SAS Enterprise Guide". Journal of the Royal Statistical Society, Series A. 172 (2): 530. doi:10.1111/j.1467-985X.2009.00588_2.x.
  11. John R. Schermerhorn (11 October 2011). Exploring Management. John Wiley & Sons. p. 3. ISBN 978-0-470-87821-7.
  12. Spector, Phil. "An Introduction to the SAS System" (PDF). University of California, Berkeley. Archived from the original (PDF) on October 12, 2013. Retrieved October 4, 2013.
  13. Chapman, David (2012). "Determine what SAS Version and Components are available" (PDF). NESUG.
  14. Hallahan, C. (1995). "Data Analysis Using SAS". Sociological Methods & Research. 23 (3): 373–391. doi:10.1177/0049124195023003006.
  15. Nourse, E. Shepley; Greenberg, Bernard G.; Cox, Gertrude M.; Mason, David D.; Grizzle, James E.; Johnson, Norman L.; Jones, Lyle V.; Monroe, John; Simons, Gordon D. (1978). "Statistical Training and Research: The University of North Carolina System". International Statistical Review / Revue Internationale de Statistique. 46 (2): 171. doi:10.2307/1402812. ISSN 0306-7734. JSTOR 1402812.
  16. Alan Agresti; Xiao-Li Meng (2 November 2012). Strength in Numbers: The Rising of Academic Statistics Departments in the U. S.: The Rising of Academic Statistics Departments in the U.S. Springer. p. 177. ISBN 978-1-4614-3649-2.
  17. SAS Institute FDA Intellectual Partnership for Efficient Regulated Research Data Archival and Analyses (PDF), Presented at Duke University, April 12, 2000, retrieved September 28, 2011
  18. Dalesio, Emery (May 5, 2001). "Little-known software giant to raise its profile". Associated Press. Retrieved April 8, 2014.
  19. Kaplan, David (January 22, 2010). "SAS: A new no. 1 best employer". Fortune. Archived from the original on November 29, 2011. Retrieved April 8, 2014.
  20. "SAS corporate timeline". March 3, 2011. Retrieved October 17, 2011.
  21. Barr, Anthony; James Goodnight (1976). "The SAS Staff". SAS 72 and SAS 76 are attributed to Barr, Goodnight, Service, Perkins, and Helwig Cite journal requires |journal= (help)
  22. (Barr & Goodnight et al. 1979:front matter) Attribution of the development of various parts of the system to Barr, Goodnight, and Sall.
  23. Oral History Interview with Jim Goodnight, Oral Histories of the American South, July 22, 1999, retrieved April 8, 2014
  24. Aster, Rick. "History of SAS version". Global Statements. Retrieved October 4, 2013.
  25. Barr, Anthony; James Goodnight; James Howard (1971). Statistical analysis system. North Carolina State University. OCLC 5728643.
  26. Service, Jolayne (1972). A User's Guide to the Statistical Analysis System. North Carolina State University.
  27. Shacklett, Mary (September 5, 2013). "See if the R language fits in your big data toolkit". The New Republic. Retrieved October 3, 2013.
  28. Barr, Anthony; James Goodnight; James Sall; John Helwig; Jane T (1979). SAS Programmer's Guide, 1979 Edition. SAS Institute, Inc. OCLC 4984363.
  29. "SAS history". SAS Institute. Retrieved October 4, 2013.
  30. Ian Cox; Marie A. Gaudard; Philip J. Ramsey; Mia L. Stephens; Leo Wright (21 December 2009). Visual Six Sigma: Making Data Analysis Lean. John Wiley & Sons. pp. 23–. ISBN 978-0-470-50691-2. Retrieved 16 November 2012.
  31. "Growing up" (PDF). JMP Forward. JMP. p. 5. Retrieved October 4, 2013.
  32. Saul, John (Winter 2010). "JMP is 20 Years Old" (PDF). JMPer Cable. Retrieved October 13, 2011.
  33. "Launches SAS JMP 8 for Mac and Linux". Ti Journal. April 11, 2009. Retrieved December 30, 2012.
  34. "New Features in JMP 9" (PDF). JMP. Retrieved December 30, 2012.
  35. Bridgewater, Adrian (November 3, 2010). "JMP Genomics 5: Data Visualization & Exploration". Dr. Dobb's Journal. Retrieved May 31, 2012.
  36. Shipp, Charles; Kirk Paul Lafler. "Proficiency in JMP Visualization" (PDF). PharmaSUG 2012. Retrieved December 30, 2012.
  37. Taylor, James (August 10, 2011). "First Look – JMP Pro". JTonEDM. Retrieved May 31, 2012.
  38. Lafler, Kirk Paul (2013). PROC SQL: Beyond the Basics Using SAS, Second Edition. SAS Institute. ISBN 978-1-61290-027-8.
  39. "Supported Operating Systems". SAS Institute. Retrieved October 6, 2012.
  40. Dalesio, Emery (February 5, 2002). "Text Miner program to bolster business intelligence". Associated Press. Retrieved April 8, 2014.
  41. Steven, Dave (July 29, 2002). "SAS is Starting to Look Even Better..." Pennsylvania State University. Retrieved October 17, 2011.
  42. Whiting, Rick (March 31, 2004). "SAS Extends Business Intelligence to the Masses". InformationWeek. Retrieved October 17, 2011.
  43. Callaghan, Dennis (September 26, 2002). "SAS to Add to Analytical CRM Arsenal". eWeek. Retrieved October 17, 2011.
  44. Gonsalves, Antone (October 10, 2008). "SAS, DataFlux Unveil 'Project Unity'". InformationWeek. Retrieved October 17, 2011.
  45. "Reference for a preliminary ruling from High Court of Justice (Chancery Division) (England and Wales) made on 11 August 2010 – SAS Institute Inc. v World Programming Ltd". European Court of Justice. Retrieved May 19, 2012.
  46. "The functionality of a computer program and the programming language cannot be protected by copyright" (PDF). European Court of Justice. Retrieved May 19, 2012.
  47. Hardy, Quentin (June 9, 2011). "SAS-We Spurned IBM, Now to Win". Forbes. Retrieved October 17, 2011.
  48. Greenberg, Paul (December 31, 2010). "The CRM Watchlist Part II: The Usual Suspects". ZDNet. Retrieved October 4, 2013.
  49. "Computing Seminars: Introduction to SAS Macro Language". UCLA Academic Technology Services. Retrieved October 4, 2013.
  50. Howson, Cindi (September 7, 2010). "SAS Takes Predictive Analytics Mainstream". InformationWeek. Retrieved October 4, 2013.
  51. New Features in JMP 9 (PDF), JMP, retrieved December 30, 2012
  52. Bridgewater, Adriian (November 3, 2010). "JMP Genomics 5: Data Visualization & Exploration". Dr. Dobb's Journal. Retrieved May 31, 2012.
  53. Laskowski, Nicole (October 26, 2011). "SAS ups 'big data' ante with high-performance computing platform". SearchBusinessAnalytics. Retrieved October 4, 2013.
  54. Sheina, Madan; Surya Mukherjee (October 17, 2011). "SAS adds in-memory to high-performance computing". Ovum.
  55. Taylor, James (November 11, 2011). "First Look – SAS Enterprise Miner 7.1". Retrieved October 4, 2013.
  56. Arellano, Nestor (October 22, 2014). "SAS expands cloud analytics business". IT World Canada. Retrieved November 13, 2014.
  57. Jackson, Joab (April 27, 2015). "SAS enlarges its palette for big data analysis". IT World. Retrieved May 22, 2015.
  58. "How old is your version of SAS? Release dates for SAS software". The DO Loop. Retrieved 2018-03-27.
  59. Whiting, Rick (May 11, 2004). "SAS Ships Customer-Intelligence App". InformationWeek. Retrieved January 7, 2014.
  60. Yasin, Rutrell (May 10, 2013). "Social network analysis, predictive coding enlisted to fight fraud". Government Computer News. Retrieved December 11, 2013.
  61. Hunsberger, Brent (August 23, 2013). "Credit card blocked? Get used to false positive fraud alerts for now". The Oregonian. Retrieved December 11, 2013.
  62. Albergotti, Reed (July 22, 2013). "IRS, States Call on IBM, LexisNexis, SAS to Fight Tax Fraud". The Wall Street Journal.
  63. Kenealy, Bill (March 25, 2009). "Assessing Business Intelligence". Insurance Networking News. Retrieved December 11, 2013.
  64. Stephani, Justin (May 10, 2012). "SAS Upgrades GRC Software Quicker Compliance". Information Management.
  65. McClean, Chris (November 30, 2011). "The Forrester Wave™: Enterprise, Governance, Risk, And Compliance Platforms, Q4 2011" (PDF). Retrieved December 12, 2013.
  66. Hui Pan, Editor. Iraq Telecom Monthly Newsletter November 2009. Information Gatekeepers Inc. pp. 5–. GGKEY:ZPZ8BD13DR8.
  67. "SAS Launches Suite Of Solutions For IT". ITManagementNews. September 22, 2004. Retrieved December 12, 2013.
  68. Gary Cokins; Karl D. Schubert; Michael H. Hugos; Randy Betancourt; Alyssa Farrell; Bill Flemming; Jonathan Hujsak (24 September 2010). CIO Best Practices: Enabling Strategic Value With Information Technology. John Wiley & Sons. pp. 64–. ISBN 978-0-470-91255-3.
  69. Brown, Timothy, Using SAS Strategically: A Case Study (PDF), NESUG, retrieved December 12, 2013
  70. "Product Review SAS SPM Strategic Performance Management". FSN. October 8, 2006. Retrieved December 12, 2013.
  71. Callaghan, Dennis. "SAS to Extend Its Supply Chain Offerings". eWeek. Retrieved December 12, 2013.
  72. Li, Kang (May 5, 2008). "Software for sustainability management unveiled". New Straits Times. p. 41.
  73. "Products & Solutions Index". SAS. Retrieved December 12, 2013.
  74. "Free SAS® Software for Higher Education, Adult Learners Now Available". www.businesswire.com (Press release). 2014-05-28. Retrieved 2019-01-06.
  75. Acock, Alan C (November 2005). "SAS, Stata, SPSS: A Comparison". Journal of Marriage and Family. 67 (4): 1093–1095. doi:10.1111/j.1741-3737.2005.00196.x.
  76. "Compare Packages". University of California, Los Angeles. Retrieved 12 January 2014.
  77. Henschen, Dough (July 26, 2011). "Low-Cost Options For Predictive Analytics Challenge SAS, IBM". InformationWeek. Retrieved January 12, 2014.
  78. Ranii, David (January 20, 2012). "SAS' revenue up 12% in 2011". The News & Observer. Raleigh, North Carolina. Retrieved January 12, 2014.
  79. Turchin, Brian. "SAS Profile -- Going Its Own Way" (PDF). Software Business Online.
  80. "Just How Big Is the Big Data Market?". ClickZ. 2014-07-07. Retrieved 7 July 2014.
  81. Vesset, Dan; David Schubmehl; Brian McDonough; Mary Wardley (June 2013). "Worldwide Business Analytics Software 2013–2017 Forecast and 2012 Vendor Shares". IDC. Retrieved October 2, 2013.
  82. Pendse, Nigel (March 7, 2008). "Consolidations in the BI industry". The OLAP Report.
  83. Schlegel, Kurt; Rita Sallam; Daniel Yuen; Joao Tapadinhas (February 5, 2013). "Magic Quadrant for Business Intelligence and Analytics Platforms". Gartner. Retrieved October 1, 2013.
  84. Dembe, A. E.; Partridge, J. S.; Geist, L. C. (2011). "Statistical software applications used in health services research: Analysis of published studies in the U.S". BMC Health Services Research. 11: 252. doi:10.1186/1472-6963-11-252. PMC 3205033. PMID 21977990.

Further reading
  • Greenberg, Bernard G.; Cox, Gertrude M.; Mason, David D.; Grizzle, James E.; Johnson, Norman L.; Jones, Lyle V.; Monroe, John; Simmons, Gordon D. Jr. (1978). Nourse, E. Shepley (ed.). "Statistical Training and Research: The University of North Carolina System". International Statistical Review. 46 (2): 171–207. doi:10.2307/1402812. JSTOR 1402812.

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