IT companies just ‘love’ the Gartner Magic Quadrant – or those companies that come out with flying colours do. What is this ‘Gartner’s Magic Quadrant’? And why should you and I be looking at it? As members of the Analytics Fraternity, we want to be abreast of the latest status of analytics soft wares. I would also like to be re-assured that my favourite software – SAS – remains the favourite in this dynamic world of never ending change.  And that I am on top of my game.

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Gartner starts its report by firmly clubbing business intelligence with Analytics . The ‘business world’ was already seeing these two together for the last couple of years and now we all do understand that data visualisation and reporting is the first steps in Analytics.

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.

However, as per Gartner’s team – ‘SAS’s dominance in predictive analytics and statistics continues to be challenged on many fronts. IBM is still the main challenger with SPSS and other analytic assets, but wide support of open-source R by large competitors, such as Oracle, SAP and other smaller vendors, will be the most serious threat in the long term. R is challenging SAS for the title of standard coding language for analytics, and is increasingly considered a credible alternative by professionals in the market, eroding SAS’s dominance in the analytics community’

In my personal view, the people who deal with ‘small data ‘  – a word that I will use to describe data that has upto  1 million rows and 1000 columns of data and can fit into an excel sheet, will be drawn to softwares that allow them to do processing on excel itself. The dominance of Microsoft office suites is hard to beat and therefore, softwares like XLSTAT or Palisade’s @Risk are bound to make huge inroads as an easy to use and implement system.

SAS and SPSS will continue to hold ground but just because of the sheer volume of data that SAS can process without a blip and the very ‘long term relationship’ style of marketing and sales that SAS practises as a company, I think SAS will grow as a 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 has extensive online help, making its usage quite like writing an open book exam .  As long as you know what you are looking for, there is near certainty of finding it on the click of the mouse. Another point in the favour of SAS will be its ability to handle the big data revolution.

I will close this article by saying that this ever changing and evolving space of technology in Analytics is going to be an interesting space to watch.

 

Interested in learning about other Analytics and Big Data tools and techniques? Click on our course links and explore more.
Jigsaw’s Data Science with SAS Course – click here.
Jigsaw’s Data Science with R Course – click here.
Jigsaw’s Big Data Course – click here.
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