What is predictive analytics?

In this tutorial we are going to explain predictive analytics and illustrate the various usages of analytics in today's Big Data environment.

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What is predictive analytics and what are its uses?

Predictive analytics is part of Data Science which reads and processes the large data sets to identify the patterns. This analysis of patterns and trends of vast data sets are done to predict future outcomes. This analysis is not 100% sure it just predicts the future outcome based on the previous trends and data analysis.

Big Data played a major role in this field because it provides the system for storing such a huge data sets and then gives the computing power for analysis of data. Hadoop cluster uses the power of a number of servers in the cluster for faster processing and analysis of data.

This article is discussing about the technologies and programming languages capable of doing predictive analytics. In this article we are giving you the details of all the major programming languages being used for predictive analysis.

Definition of Predictive Analytics

Predictive analytics is highly computational activity which involves the analysis of existing data sets with a goal of identifying the trends and patterns. Analysis of existing data and finding a trends is very important in the data science because these trends are used for predict the future outcome based on the analyzed trends and patterns.

The predictive analytics is not absolute science, rather it provides reliable forecast for the companies. This forecast is very important and companies can use this information to decide future course of their business operations.

Predictive Analytics uses:

  • Predictive Modeling
  • Machine Learning
  • Data Mining

Above 3 techniques are the core of predictive analytics which analyzes the large data sets and come out with valuable predictions.

Methods of Predictive Analytics

Predictive Analytics uses mathematics and several algorithm to find out the various trends and patterns among the previous data and predicts the future outcome. It uses the major variables, different measurable relational ship among the data  sets to predict the future outcome.

Its uses the statistical model to predict from the existing data sets. It can also rely on the real-time data for smart prediction and this increases the accuracy of the prediction.

The Business Predictive Analytic finds the patterns hidden in the historical data comes out with risks and opportunities. This helps as a guide in decision making related to the business.

Uses of Predictive analytics in industries

Predictive analytics can be used in following industries:

  • Actuarial Science
  • Marketing
  • Financial Services
  • Insurance
  • Telecommunications
  • Retail
  • Travel
  • Mobility
  • Healthcare
  • Child protection
  • Pharmaceuticals
  • Capacity planning
  • Predictive Analytics in Agriculture
  • Predictive Analytics in E-commerce

Predictive analytics can be all the places where past data is analyzed for making future decisions. Its really top tool for being used by various industries to analyze previous data and making decision on the future course of action.

Uses of Predictive Analytics in Marketing

The predictive analytics with Big Data is one of the most valuable tool for marketing, it allows the business owners to very accurately predict the behavior of the customer. Marketers are using these predictions for designing best marketing plan for their products, they can offer products to the user might buy.

Here are the most uses of Predictive Analytics in Marketing:

  • Understanding and predicting customer behavior
  • Offering relevant products to users
  • Determining/predicting behavior of customer in case promotional offer
  • Predicting the customer about becoming loyal customer
  • Predicting the up-selling and cross-selling of products
  • Predicting various up-coming opportunities

So, the uses of Predictive Analytics in Marketing are unlimited.

Tools/Programming languages of Predictive Analytics

There are many tools for Predictive Analytic, both commercial and open source. You can use these tools in your applications. Here are the Open Source Predictive Analytics tools:

  • Apache Mahout - Its distributed machine learning framework from Apache software foundation
     
  • GNU Octave - GNU Octave is programming language which is used for scientific computing and can be used for Predictive Analytics
     
  • KNIME - KNIME is open source leading Analytics Platform
     
  • OpenNN - OpenNN library implements neural network and used in machine learning.
     
  • Orange  - Orange is a tool for data mining and Predictive Analytics
     
  • R - This very popular programming language for Data Analytics and machine learning.
     
  • scikit-learn - Its machine learning framework in python.
     
  • Weka - Weka is written in Java and its a suite for machine learning

In this section we learned about the Predictive Analytics, check our Big Data tutorials section.

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What is predictive analytics?

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