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The buzz word everywhere is analytics but it’s only when your interest is piqued and you decide to investigate a little further that the realm of all analytics software tools opens up. Among these, SAS you will soon find is hard to ignore as an integral part of all analytics domains.
SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence Market. Through innovative solutions, SAS helps customers at more than 70,000 sites improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world the power to use data to make informed business choices.
SAS or statistical analysis system as it was originally called is a software suite or a set of solutions developed by the SAS Institute to analyse and interpret large sets of data by business users enterprise-wide. It enables them to derive conclusions and make strategic recommendations to improve business performance. The many tasks SAS can perform include data entry, retrieval, and management, report writing and graphics, statistical and mathematical analysis business planning, forecasting, and decision support.
Origin of SAS
The major contender in the world of analytics today had its origins in very humble beginnings.
The SAS seed was sown in 1966 when Anthony Barr at North Carolina University started a program to analyze agricultural data and increase crop yields. Barr was later joined by James Goodnight, a student at the time who helped program statistical routines into the software, thus putting the duo at the helm of the project. Though the project initially lost it’s funding from the National Institute of Health, the University Statisticians of the Southern Experiment Stations extended their help to finance the project the following year. Work thereafter continued uninterrupted with more people joining and contributing extensively. A few of these notable contributors were John Sall who joined in 1973, Caroll G. Perkins who contributed to SAS’ early programming and Jolayne W. Service and Jane T. Helwig who created SAS’ first documentation.
Eventually in 1976, Barr, Goodnight, Sall, and Helwig took the project out of North Carolina State and incorporated SAS Institute, Inc.
Why opt for SAS?
Gartner research in it’s issue states that SAS’s strengths in the Industry still remains undisputed in several spheres of analytics.
But why should you or I go by what Gartner perceives?
This would require a short introduction to Gartner itself. Gartner is an information technology research and advisory company providing technology related insight. Gartner uses what it calls Magic Quadrants for visualization of its market analysis results. Magic Quadrants are a culmination of research in a specific market, giving you a wide-angle view of the relative positions of the market’s competitors.
To quote from the report on the strengths of SAS :-
- SAS gets high marks for its global footprint and broad industry initiatives. The solution-oriented analytic application approach to the market is a differentiator, giving the company the advantage of having a wide variety of cross-functional and vertically specific analytic applications out of the box for a wide variety of industries, including financial services, life sciences, retail, communications and manufacturing. Thus, SAS’s sales processes can be diverted from tool features and price comparisons to a discussion of potential business value of solutions and industry expertise. While others are also adopting this approach, SAS remains in the lead.
- In 2012, SAS announced Visual Analytics, the new data discovery product that merges dashboard design with diagnostic analytics and the use of predictive models — a possibility not yet available in some of its competitors’ tools.
From our viewpoint, the world of data can be divided into three parts –
- Small data- a word that will be used to define data that has upto 1 million rows and few hundred columns of data and can fit into an excel sheet, will be drawn to softwares that allow them to do processing on excel itself
- Large data– a word that will be used to define data that has a few million rows and a few thousand columns of data and will often be found in ERP system tables and in the EDW (enterprise wide data ware house). The common softwares to analyse this data is SAS, SPSS, Minitab, Stata, Systat etc. The size of the data most likely would be around 1 GB.
- Big Data – a word used to define data that is huge, much likely run into a few GBs and require systems like Hadoop, Teradata etc. to hold and manage.
For Large data, SAS and SPSS will continue to hold ground but SAS’s ability to process large volumes of data without a blip and the very ‘long term relationship’ style of marketing and sales that SAS practises as a company, will fuel SAS as the most popular and widespread SAAS in the area of Analytics. Sheer acceptability in the industry will snowball the widespread usage of SAS, quite like MS office. Also, SAS’s extensive online help makes its usage quite like writing an open book exam. As long as you know what you are looking for, there is near certainty you will find it on a click of the mouse.
To conclude, another stronghold for SAS will be its ability to handle the big data revolution.
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