SAS, Python, and R are the 3 most data analysis language. For a newbie in the domain of data science, making the right priority can turn to be an almost impossible task. Paragraphs underneath shall provide insight on all these tools and compare between them, so that you can decide your priority tool for learning.
R is the language, meant to serve Statistical data analysis. It is an open-source and free language that finds application to analyze data. Python is another open-source and free language that serves multiple utilities in the domain of Data Science. SAS stands as the market leader, when it comes to the organizational analytical tools. This tool features a robust GUI interface and serves arrays of statistical functions. Compared among these 3 tools, SAS is the easiest language to learn.
Industries where these tools find applications
Big Organizations prefers SAS as it offers robust user support services and for this reason, this application enjoys an edge in the domain of financial services as well as in marketing companies to whom the cost of the tool is not the primary point of consideration.
On the other hand, Pyhton & R are mostly availed by the startup and smaller companies that always hold a tight budget for investing in the tools. Coming to the perspectives of Telecom and Technology companies, wherein, Data Scientists will require processing a huge volume of unstructured Data, Python & R are the preferred languages as it supports machine learning.
Cost of the tools and ease of learning
Among these 3 tools, SAS is the most expensive and hence, its application is restricted among the larger organizations that are cash rich. On the other hand, Python & R, being Free software, are availed universally. In terms of the ease of learning, SAS is the top choice. It features an easy-to-use interface and hence, even if you don’t hold knowledge in programming, you can still manage to learn this software.
Capabilities in terms of Data handling
SAS puts a gallant performance in accessing Sequential data as well as accessing database through SQL. The interface with drag & drop functions make the application, extremely easy for the users. Hence, they can develop quality statistical models within the shortest time span.
R holds the reputation for its feature of In-memory analytics and the major application of this software involves those instances that involve a dedicated server.
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Job scenario and availability of user support services
SAS finds application in the biggest organizations across the world and to sound specific, in large organizations that majorly deals with structured data. On the other hand, start ups & smaller enterprises or companies, majorly dealing with unstructured data, prefers to opt for Pyhton and R.
SAS has got a fair extent of the user community and holds a reputation for offering delightful support services to the users. On the other hand, though Python & R feature equally glorious standing in terms of community, they lack in terms of the user support functions.
The points stated above suggest that you should decide your priority for learning, considering your respective needs.
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