Published on Jul 19,2018
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In today’s fast-changing Big Data world, mastering the right analytical tool holds the key to a successful career. Before acquiring new data analytics skills, you need to know about the prospects of relevant tools in the job market. Let’s look at why we need R Tutorial.

R – World’s Most Powerful Programming Language for Statistical Computing and Machine Learning

The usage of ‘R’ as a data analytical tool is on the rise, and clearly marching ahead of other statistical tools like Minitab and Statistica. What is more interesting to note is the upward curve of R, which is almost rising up at a 90 ° angle. This shows the popularity of R as an analytical tool. Further analysis from Rexter points states that R is going to be the most used analytical language of choice in the coming years.

R - World’s Most Powerful Programming Language for Statistical Computing and Machine Learning

Owing to its popularity, R has a thriving global community of users, developers and contributors. Analysts and data professionals can’t ignore the current status or the future potential of  R. R tutorial empowers Business Analysts, Data Analysts, and IT Managers in making accurate, advanced, and predictive business forecasts, which can steer their companies ahead of their competitors.

R is the Preferred Industry Choice

R is highly used as a data mining tool compared to its major competitors, both as a primary and as a secondary tool.

R is the Preferred Industry Choice

 Here are some excerpt on surveys that denote the same:

  • As per the Rexter poll, a whopping 85% of users are either satisfied or extremely satisfied with R, reinforcing its popularity status in the industry.
  • Forrester Research reports that R is by far the most popular predictive analytics platform.

As a business analytical tool, R is on the upward curve, given its ability to work with Hadoop distributions from Cloudera and Hortonworks. It can also work with enterprise data warehouse systems from Teradata and IBM Netezza.

Land One of the Highest Paying Jobs in the World – Data Scientist 

It is a known fact that Data Scientists are the most highly paid IT professionals in the world today. In spite of the humongous pay scale, there is still huge gap between the skill demand and the skill availability. And by next year, as per a Gartner’s report, there will be a huge talent crunch. R tutorial will make you eligible for all the currently available data professional jobs and those coming up.

Land One of the Highest Paying Jobs in the World

Data Science is a new discipline and this talent scarcity is expected. Training is the smartest way to make the most of this opportunity. Those who aspire to become data scientists, can brush up their data skills with ‘Business analytics with R’ Tutorial, and mold themselves for the most coveted jobs of the 21st century.

R is already the industry leader in business analytics. Learning ‘Business Analytics with R’ will enable professionals to offer deeper insights to help companies maximize revenue from raw data.That is the standard industry expectation from a data scientist. A tutorial on Business Analytics with R can help you get precisely there.

R Job Trend

Companies Increasingly Using  R

Business Analytics is essential for companies as they need to extract business insights to implement strategies to take their business forward and gain a competitive edge. ‘Business Analytics with R’ endows you with the added advantage of knowing the most popular data mining tool and thereby  increasing your employability by leaps and bounds. Some of the industry giants using R for business analytics are:

  • Microsoft Bing
  • Google
  • Facebook
  • Twitter
  • ANZ Bank
  • The New York Times

Got a question for us?? Mention them in the comments section and we will get back to you.

Edureka has a specially curated Data Science course which helps you gain expertise in Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, Naive Bayes. You’ll learn the concepts of Statistics, Time Series, Text Mining and an introduction to Deep Learning as well. New batches for this course are starting soon!!

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Published on Jul 19,2018

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