How is prediction made with Big Data Analytics?

Big Data Analytics employ predictive analytics for retrieving information from the existing sets of data for analyzing patterns and make predictions about the results and trends that can emerge in future. The predictive analytics doesn’t pronounce future happenings with surety. It is just a forecast of what may happen in future if situations follow the predicted sequence based upon the risk and opportunity assessment.

The Potential Of Predictive Analytics

It is an area of data mining that is associated with extracting information from large quantities of data sets and capturing relationships between the predicted variables from the historical data and explanatory variables to fully exploit them and predict a future outcome. However, the usability and accuracy of the results are largely dependent on the quality of assumptions and the level of data analysis. 

Predictive analytics is a term way broader than forecasting. It is basically a technology that enables businesses learn from their experience to predict behaviour of the target market segment for driving better decision making. Many industry experts believe that predictive analytics help in predicting and preventing potential threats to attain almost zero break-down and after getting further collaborated with prescriptive analytics; it will boost its value and will trigger optimised business decisions.

Predictive analytics engulfs several kinds of statistical techniques such as machine learning, data mining and predictive modelling that assist in reliable analysis of existing and past facts along with trends to make future predictions. Businesses using Big Data largely utilise the potential of the predictive analytics as they fully explore the patterns observed in the past to effectively evaluate the forthcoming threats and opportunities. 

These predictive models establish relationships between various determinants to easy allow analysis of the risk of potential threats related with a particular set of conditions, thus guiding the decision making process in the most efficient manner.  Product purchasing trends, buying behavior of customers, survey results and social media data are being fully harnessed by businesses to make progressive changes in the product development and innovation, amendments in pricing structure, introduce smarter and modern ways of marketing, etc.

Big Data & Predictive Analytics

Empowering Big Data is predictive analytics that makes use of both stored and real time data to help businesses in taking crucial decisions, which can aid in advantageously utilising impending opportunities while finding ways to counter the threats. Businesses accumulate humongous volumes of data every second in both structured and unstructured form. Collection, analysing and mining these massive amounts of data from Big Data sources such as social network, Internet search indexing, web logs, military surveillance, call detail records, etc. is now feasible with predictive analytics.

After deploying the Big Data techniques such as Hadoop, MapReduce and text analytics, businesses get valuable insights in real time. Since running predictive algorithms on streaming data is possible, this real time data is then combined with the historical data by predictive analytics. This results in predicting future events to understand the effectiveness of their current decisions and analyse the responses of the target market for the various marketing moves of the businesses. 

In terms of application, predictive analytics is versatile in nature. Predictive analytics has been successfully deployed in various verticals and has shown highly positive results in areas such as clinical decision support systems, analytical customer relationship management (CRM), collection analytics, child protection, fraud detection, customer retention, direct marketing, project risk management, portfolio/ product/ economy level prediction, etc.