For a lot of quantitative corporate personnel, the raging debate between the tools of choice for analytics has been known to cause some rival enthusiasm instead of the age-old political debates on Thanksgiving!
The SAS vs. R debate was already hotly underway for the past couple of years, but recently many analytics professionals and aspiring analysts have requested us to include a comparison of Python in our debates. So, we decided to keep things light and simple and only asked a single question – “which analytics tool do your prefer to use: SAS, R Programming or Python?”
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Gradually our survey results have been showing a growing demand for open source tools over the past few years. In fact so much so, that this year almost 61.3% of respondents in a survey conducted by KDnuggets chose R and Python over 38.6 percent of people still opting for SAS. As it is SAS is a great tool for large companies to conduct their data analytics.
Are you keen on learning more about these numbers? So were we, so tallied a few survey results and opinions of analytics professionals to determine which is the better data analytics tool to learn first. And here is what we found…
In this era of technology people don’t need to move across continents or shift to other cities to gain knowledge. They can get all the information they need just by logging into the web and clicking a few links. So if you are interested in the field of data analysis and want to know all the latest happenings in this field just register for the free live demo session organized by DexLab Analytics on Credit Risk Modelling with SAS and brush up on your data analysis skills. This real time demo session will take place on the 15th of October at 5 P.M. sharp. Drop us an email at firstname.lastname@example.org to register for this event or fill up the contact us form in our website.
For more details about the demo session visit us at:
If you are new to the glittering world of the corporate community, you may have come across the words like data analysis coaching, SAS training centres and may even know a few of your colleagues or batch-mates who have already enrolled with such institutes to make their resume look more impressive and smoothen the path to that long awaited promotion they have been working hard for.
But why is SAS training necessary? And how would it impact your business?
The fact that knowledge in the field of data analysis or SAS could be important for the development of your company is nothing short of an understatement. It is a no-brainer that no commercial firm can hope to survive in the market without having their data analyzed. If you still find yourself ambitious in giving it a shot, we suggest you imagine the following two scenarios:
- Imagine you have a pharmaceutical company, and are working on a new drug that can potentially cure cancer. And you are currently running drug trials on say, more than 500 patients. This massive bunch of patients will generate a huge bulk of data.
- There may be a fruit juice company with plans to expand their flavor options by launching a new flavor of fruit juice. In order to test the markets, and to gauge the procurability of this flavor they are running a survey to determine the profitability linked to this flavor. This would generate a huge list of data to keep track of at all times.
- The sales director of your company is aware of discrepancies with a certain popular product; it is a serious situation with the company reputation and brand value at stake. But he has not initiated a market research analysis program to enable him to draw valuable conclusions. What will happen?
The above sample scenarios are strong enough testimonies to the fact that market research and data analysis form the backbone of all companies. Hence, it is apparent that skills in data analysis tools such as SAS knowledge is an invaluable skill in any intelligent professional.
What a standard SAS teaching institute should provide in their curriculum?
- How to automate work using MS Excel
- How to create visually pleasing dashboards to make your webpage more appealing to potential leads
- Understanding Logistic regression and Ace Learning
- Perfecting SAS software understanding and R skills
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