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SAS vs Python for Analytics


Today we are going to have a very interesting topic to discuss SAS vs Python for Analytics which is about analyzing the two important data science tools SAS and Python. We will be talking about their features, how they work, and more.

All about SAS:

If we compare SAS vs Python for Analytics. SAS is an acronym for Statistical Analytics System and is commercial software that has been developed for handling complex analytics, statistical modeling, and other statistical functions. They are mostly used by large corporations and especially banks, insurance sectors, and healthcare. Know that SAS is neither open-source nor free and not cheap as well because it is the greatest deterrent for small businesses. It is also an important system for start-ups who wish to adopt it and get their things up on track.

The SAS has been slowly upgrading itself but still, it hasn’t upgraded to AI and other machine learning tools like R and Python. But there are other products that SAS has started offering to its customers. This includes customer intelligence, security intelligence, risk management, and big data capabilities. Delve into the world of data with our comprehensive Explore SAS Coding Courses.

What Components Make up the SAS?

SAS has been made up of more than 200 components which include the below-mentioned as well.

  • Base SAS programming language for data management and analytics.
  • SAS/INSIGHT used in data mining.
  • STAT used in statistical analysis.
  • SAS EBI is used in business intelligence applications.

Features of SAS:

The following are the features of SAS.

  • It is not open-source hence it is not free.
  • It offers high stability and data security.
  • Similarly, SAS offers other features as well including customer support, technical support, and other software maintenance services throughout.
  • It is cloud compatible through SAS Viya which enables all the programmers to process commands in the cloud.
  • Furthermore, it has integrated AI and ML functionalities although they haven’t been established yet.

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If We Compare SAS vs Python for Analytics. Python is known to be an open-source object-oriented programming language that has become quite popular among data scientists and many software developers. Python has been preferred by the majority of people due to a variety of reasons like supporting structured, object-oriented, and functional programming among others. And also integrating well with existing infrastructure. You might also be interested in Google Data Analytics Certificate.

Popular Python Libraries:

The popular Python libraries include the following.

      • NumPy is used for numerical computing.
      • Pandas are being used for data manipulation.
      • Scikit Learn for machine learning.
      • Matplotlib that we used for visualizing data.
      • And lastly, Tensorflow is used for machine learning operations and numerical computing.

Features of Python:

SAS vs Python for Analytics Python offers a variety of features.

      • It is very easy to use and easy to learn syntax that is perfect for beginners who have basic coding knowledge. You can also find out SAS Programmer Salary Statistics here.
      • It contains a large number of libraries including those of AI and ML.
      • Similarly, it is an interpreted language.
      • It is supported by many operating systems that include Windows, Linus, and Mac platforms.
      • Python is a very fast and highly scalable programming language.
      • It comes with quite a range of visualization, data analysis, and data manipulation functions. Unlock the potential of Python for machine learning with expert-recommended free courses, designed to help you gain proficiency in data analysis and predictive modeling without any financial investment.


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So in the end SAS vs Python for Analytics we would say that the industry is shifting towards open-source technology. And what we were able to understand is tools like Python are versatile in nature and are most preferred for data science. Whereas the SAS is more suited for statistical analysis and business intelligence. Thereby, we can conclude that a beginner who is pursuing data science would gain more benefit in learning Python. Whereas, if they intend to add more opportunities for themselves, then adding SAS to their skill set is the answer. In short, both SAS and Python are quite competitive and can help beginners and even professionals to add opportunities for themselves. So learn to use both SAS and Python now, stay home, stay safe, and never stop learning. Whether you decide to enroll in a Free Online course with Certificates and study at your ease and pace or enroll in a SAS vs Python for Analytics courses where you have to follow a proper schedule.