What Makes SAS Popular And How Does It Vary From R And Python?
One of the most effective technologies today is data science, which has developed over time. The area uses technologies like programming languages R or Python or statistical analytics tool SAS, as well as statistical knowledge, machine learning algorithms, and data scientists to sift through vast amounts of structured and unstructured data to uncover patterns. SAS is a closed-source tool, whereas R and Python are open-source ones. In this blog, we have discussed what makes SAS popular and how it varies from R and Python, to learn more, join SAS Training In Chennai offered by FITA Academy.
Why SAS?
The fact that SAS allows access to data in any format is one of its most vital advantages. Either SAS tables or Excel worksheets can be used as the format. With SAS, organising and altering data to find critical information is possible. Additionally, it makes it simpler to add new columns and combine them with other data when creating a data subset. Companies in the financial and marketing sectors utilise SAS for analysing and comprehending client services.
The drawback of SAS is that it costs a lot to buy commercial software. This is why new and small businesses cannot use it. They rely on free downloads instead. Software like Python and R. However, SAS offers a wide range of product parts to users. These include econometrics, IoT analytics, customer intelligence tools, decision management tools, and asset performance analytics.
How Does It Vary From R And Python?
R is typically utilised for in-memory analytics when a standalone server is required for data processing operations. It is helpful for statistical modelling, information visualisation, and large-scale data analysis. Because of its vibrant community and data mining tools, Python is a multifunctional, adaptable programming language that has grown immensely popular in data science. Numerous libraries that are supported by it enable users to work in various domains, including data wrangling, data filtering, data transformation, predictive analytics, machine learning, etc.
R’s libraries include Ggplot2, Dplyr, and Tidyr, while Python’s include Numpy, Pandas, Matplotlib, and TensorFlow. Since SAS does not require programming knowledge to acquire, it is the easiest of the three languages to learn. It features an easy-to-use GUI (Graphical User Interface) built-in and a programming language similar to SQL. Additionally, components may be picked up and used immediately without worrying about the coding aspect, thanks to the drag-and-drop capability. This facilitates the rapid development of improved statistical models. Additionally, SAS has a specialised support staff that may respond to user inquiries directly. SAS provides customers with SAS Viya, a feature-rich cloud platform that enables executives, data scientists, and business analysts to interact and work on outcomes.
Thus, some reasons that make SAS popular and how it varies from R and Python. Enrolling in the Best Training Institute In Chennai can give you the skills and knowledge to excel in this field.