Predictive Analysis with Big Data Analytics Using R Programming Language

Posted by vikas sharma on November 13th, 2019

Gone are the days when Excel was used to analyze large data. The present era talks about using Predictive analysis with big data analytics to get the best results. However, with the growing trends, the use of the R programming language is vastly seen. It aids in big data and other statistical analysis assignments. Let us understand what Predictive analysis when combined with big data analytics, can do for us. Also, know how the R programming language helps in great learning.

Big Data Analytics Certification- Hear What It Says

It is a known fact now as for how the process of inspecting large and varied data is used to uncover correlations, study market trends, sees the customer preferences, hidden patterns, etc. Big data analytics is the trump card that helps the optimizing business processes and opportunities.  It is through the data received from the Big data analytics report that retailers start stocking their goods, employers begin taking action towards their decision-making, recruits happen by market trends. In a nutshell, there is a huge role played by Big Data analytics in the business world.  The 5 Vs of big data circles are studied mainly, i.e. volume, variety, velocity, veracity and value to get the right information.

The Advanced Analytic

Predictive analytics is known as advanced analytics. Analytics is used to make predictions. It uses several techniques to gather data. The use of data mining, machine learning, artificial intelligence, statistics, etc. is vastly used to make the prognosis. In short, it determines which data is helpful from a prediction point of view so that it gives the desired outcome. The result that is obtained from Predictive analytics is the combined effort of Big Data and business intelligence.  Predictive analytics help in the big way to entice new customers helps the market with product performance data etc. It is a way of staying ahead in the competition and know one step forward while your competitor is busy with the past data and present scenario.

The Emergence of R Programming Language

For faster, cleaner and better analytic tools, the development of the R programming language has benefited at large. The programming language, as well as software, is widely used for analytics and graphics. For data miners, it is an asset that helps in data analysis and presentations. The motive of R programming language origin was to benefit statisticians to do statistical analysis and predictive analytics. However, looking at its scope, the language has been the favorite for data modeling, predictive analysis with big data analytics too.

Benefits of Using R Programming Language

This programming language has an active community, meaning, it is an open-source tool that helps to build a rapid prototype and provides a great learning experience. It thereby shows the management of the benefits of predictive analytics. Therefore on the occurrence of a problem, by just stating on the message board, the doubts are solved. Plus what's more, you do not have to invest in any other software for any further prototype, your data scientist or statisticians or in that case business analysts will be able to help you.

What Happens When Predictive Analysis With Big Data Analytics Using R Programming Language Is Combined?

R programming language helps with pre-built predictive tools. It aids in the creation of the fastest platform for predictive analytics. There can be a single click sharing of analytic applications. This makes it easy to access the data and does not require a data-miner to be nearby to give them the data that the decision-makers need.

The market needs fast and relevant data. With the help of R programming language and predictive analysis, fast access to all relevant data is possible. This day, R is used widely by the companies to get a comprehensive study of the market. R is a free programming language is used for statistical modeling, visualization and of course, data analysis. It primarily helps in the predictive world. Many companies such as Facebook are using R to study the behavioral analysis of users on their status updates and profile pictures; on the other hand, Google is using R to analyze the advertising effectiveness and forecasting on it. Twitter learns about data visualization while Microsoft has indulged in R for a variety of purposes.

R Programming Language's Scope On Big Data Analytics

With around 2.5 quintillion bytes of data on a daily basis, R is a dominant source language for data-driven decision making. The language is robust and has data handling features that makes it alluring for most of the organizations. While incorporating predictive analytics with big data analytics, R works as an open-source comprehensive data analyst. It helps in visualizing, manipulating and analyzing the dataset. R has over 5000+ data packages and the dominant scripting language. This makes it easy for the data scientist to grasp the data efficiently and can handle extensive and complex data sets effortlessly. The language also allows the creation of functions and packages. The incredible part of this language is one can install it without purchasing the license. Since it is a cross-platform tool, you can efficiently use it on your computer or laptop and can run smoothly on Windows, Mac OS X, and import data from Microsoft Excel, MySQL, and Oracle, etc.

Wrap Up

Due to the R programming language's greater visualization and more capabilities, businesses prefer following this language. The feature of open source allows fixing bugs if any. The rise of R has benefited predictive analysis with big data analytics in a more excellent way. Today the demand for R programmer is more. The golden child of data science is R, and the language is best to use for resource-intensive simulations. It works best on high-performance computer clusters. The most striking part of R is that it can be embedded into word-processing documents, and trust me, publishers love R for that! R has emerged as one indispensable language amongst the programmers ever since 1995. If you are looking for predictive analytics great learning with a healthy package ecosystem and graphics, with ace security and memory, R is the answer to all.