Despite the insurgence of tremendous competition SAS remains to feature one of the most trusted and most used programming languages as far as advanced analytics and data science are concerned. It is important for us to notice that SAS has been in the market as a leading language for about two decades. This shows that how adaptable and plastic it has been throughout the time in an industry that is characterized by change and development. Data science has found its way into more corners of the world than its first practitioners might have imagined, and it has become a niche area of concentration for most industries. It is hard to find an organization that has not turned to big data analytics as an indispensable part of the enterprise and we know very well that SAS training can get someone placed in the big data industry. Advanced analytics is something that most of the world is yet to wake up to or even if most companies know the perks of advanced analytics many cannot afford it. The knowledge of SAS can lead you to the very niche of advanced analytics and data science.
If you know SAS, you are in demand
Only if you go through the listings of data science jobs in various job portals, you will come across the mention of SAS skills a huge number of times. It is true that with the success of R and Python as open source, cost effective tools for data processing, management and analysis, a lot of small sized companies and start ups are going for these languages; the cream of the jobs still waits for the candidates with SAS training. Even if your company uses other languages for certain projects, chances are that they count on SAS as the single language with fantastic organization.
It is one of the best in handling data
SAS can read data from all sorts of data bases and it is evidently an excellent handler of data or we should say that you can be an excellent handler of data powered by SAS training. It is capable of pulling off parallel computation as well as processing the data on RAM. You can use it for complex simulations and for judging probability of distribution of data; all of these culminate in the attainment of data driven insights that every enterprise is looking for.
With deep knowledge you can manipulate the functionalities
SAS is a software system with efficient functional and graphical capabilities. Although it might seem to be a bit hard to customize the functionalities initially but with elaborate knowledge of the SAS graphic package it should not be very difficult for a user. A proper SAS training facility will walk you through the various alleys of possibilities and help you achieve the best results in real time projects.
You are powered by an efficient customer service facility
In spite of the fact that SAS is the most expensive option for data science programming companies which can afford it go for it because once it is bought and installed they do not need to be bothered about functionality. An efficient customer support unit is responsible for the smooth operations of the SAS tools. They help you with operation, adaptation of new techniques, contractual intricacies and more. Basically you can concentrate on the main job because the rest is well taken care of.
SAS follows the global lead
Since SAS features a closed system, it is on the slower side when it comes to catching up with the constantly evolving techniques and technologies in this highly fluid industry. But when it comes to handling of large scale projects with plenty of stake holders, one cannot just bank upon an untested technique; adventures are not always welcome for businessmen. SAS adapts the technology and brings out the complete new package with proper technical support and assurance. It may not be the fastest to adapt technological advancements but it arguably is the most reliable.
Continuous researches in the field of advanced analytics has made it a field an extremely volatile one. With AI and machine learning threatening the human work force one might have the impression that the large skill gap in the field of analytics will soon dissolve. But if you look from a global perspective, most of the world has not even started to use data science actively; there is a great lot of opportunities yet to come in display.