If
you are already into data science basics, you will be torn between picking and
leaning a programming language. 3 out of 5 data analysts would recommend you to
learn R programming. The other two could offer advises on Python and SAS course. In this article, we
will do a masterful dissection of R versus SAS programming. Data science using
SAS may not find many takers initially but it’s certainly worth taking a shot
at learning on this platform.
What to do: Data Science Using SAS or R?
Let’s make a clear distinction.
For
beginners, R is an open source programming platform that keeps evolving every
hour, thanks to the contribution from the community of researchers,
programmers, professors and scientists. On the other hand, SAS is a proprietary
tool provided by SAS, a leader in Analytics for many years. SAS already
employs 12000+ employees who are mostly data scientist and programmers from all
spheres of the industry.
Some
fast facts on SAS:
- · Number of Countries Installed: SAS has customers in 146 countries.
- · Total Worldwide Customer Sites: SAS software is installed at more
than 83,000 business, government and university sites.
- · Fortune Global 500® Customers: 96 of the top 100 companies on the
2017 Fortune Global 500® are SAS customers.
In
its current form, R is extensively used for statistical analysis, graphical
representations, and data reporting.
SAS versus R is just a myth. Both work well!
SAS
is not just another programming language applied to validate data from the
spreadsheets and databases? The output from SAS is projected in the form of
statistical analysis in tables and graphs and as RTF, HTML, and PDF docs. SAS
certified data analysts are considered at the pinnacle of the data science
industry. You can manage Big Data, Visual Data Analytics and Forecasting
techniques at the push of a button. On top of it, you will be designing your
own customized dashboards for your own Business Analytics teams.
Why R Programming for Data Science?
Compared
to R and other programming languages, SAS offers a wide range of benefits to
learners and customers. The biggest advantage of learning SAS is its
industry-relevance and contemporary analytics that can be learned from the
dashboards.
On
the other hand, R is an open source programming language which means this is way
better at handling Big Data queries in a structured manner compared to SAS!
In
data science, it’s the ability of the platform to present data in a visually
interactive manner that wins. SAS and R do just that.
Both
SAS and R are great at handling graphical capabilities that can be integrated
with other visualization and business intelligence tools.
R
has a seamless integration to Big Data communities such as Hadoop, it’s the
industry application of the open source language that is most preferred here.
By learning R with Python applications, Data analysts could have a direct
access to most products and services offered from the company’s stable.
These
include:
- ·
Machine learning and AI
- ·
Customer Intelligence
- ·
Visual Statistics
- ·
Advanced Analytics
- ·
Cloud and Risk management
- ·
Internet of Things
If you go by industry
trends, R is definitely easier to learn, but learning about SAS is also worth
the effort. In an online R Course, it will pay off the dividends quicker with the
existing cool job roles available in the Data Science industry already.
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