The Dilemma of Data Science: SAS or R or Python
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.
Read Also: 13 Advantages of R over Excel in 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…
Big Data’s Evolution in Business Decision Making
We have all established that Big Data is big and all the noise about Big Data is not just hype but reality. With the increase in technology the data generated on Earth is doubling in every 40 months and huge heaps of data keeps coming in from multiple sources. Let’s look at some data to really understand how Big Data is evolving:
- The population of the world is 7 billion, and out of these 7 billion, 5.1 billion people use a smart phone device.
- On an average everyday almost 11 billion texts are sent across the globe.
- The global number of Google searches everyday is 5 billion
But there is an imbalance as we have been creating data but not consuming it enough for proper use. We generate 25 quintillion bytes of data daily through our regular online activities including online communications, online behaviour, video streaming services and much more.
Studies carried out in 2012 showed that the world generated more than 2 zetabytes of data which is roughly equal to 2 trillion gigabytes. By the year 2020, we will generate 35 trillions of data and to manage this growing amount of data we will need 10 times the servers we use now and at least 50 times more data management systems and 75 times the files to manage it all.
The industry is still not equipped to handle such an explosion of data as 80% of it is unstructured data. It is beyond the scope of traditional statistical analysis tools to handle this amount of data as it is too complicated and unorganized.
The talent pool required to effectively manage Big Data will fall short by at least 100 thousand minds as there are only 500 thousand computer scientists but less than 3000 mathematicians. But to truly utilize the complete potential of Big Data we need more human resource and more tools.
The solution to tackle this even bigger problem of Big Data is Big Data Analytics. It is fresh new way of thinking about the company objectives and the strategies created to achieve them. Big Data analytics is the answer behind where the hidden opportunities lie.
SAS, R programming , Hadoop, Pig, Spark and Hive are a few advanced tools that are currently in use in the data analysis industry. SAS experts are higly in demand in the job market recently as it is slowly emerging to be an increasingly popular tool to handle data analysis problems. To learn more about SAS training institutes follow our latest posts in DexLab Analytics.
For more information please read our blog at http://www.dexlabanalytics.com/blog/the-evolution-of-big-data-in-business-decision-making
Things to judge in SAS training centres
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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