By definition, big data analysis is the examination of very large data. The main objective the big data analysis as a platform is to reveal patterns that are hidden, possible correlations, trend analyses and preferences among customers and suppliers. The information obtained is helpful in making business decisions.
The benefits that big data analysis accrues to organizations are new income streams and opportunities, enhanced customer engagement and service, operational efficiency is improved and have a competitive edge over your business rivals.
Big data analysis lends a crucial help to those charged with governance to analyze the huge volumes of data which normally escape review when business intelligence and other applications are used. Big data analysis will make it possible for the following to be analyzed: customers’ emails, responses from surveys, call details and click stream generated by Internet among many others. The following are areas where big data analysis have been applied in the world:
Transport and Logistics
A practical example how big data analysis can be useful is during major sporting events such as the world cup and Olympic Games. The number of visitors expected in the hosting cities and countries normally run into millions.
The organizers of these events will use data from previous competitions to forecast the number of people expected hence work on modalities for accommodations, transport from and to the sporting arenas.
Logistics companies operate across the globe and will use big data analysis to know the most effective routes and the ideal time to do shipping. The companies, are, therefore, to optimize on route management hence cutting costs and growing their bottom lines.
Risk Management and Fraud Detection
The debts are crippling many of organizations. Invoices are not being collected and loans not being repaid. Organizations and in particular banks are able to analyze the spending habits of their clients and other information. They also use this data to segregate clients into different strata before giving them loans. Those found to be high are either completely avoided or asked to bring additional collateral.
Before a risk is covered by the insurance company, a lot of big data analyses is done. Insurance companies can know information on claims, risk and actuarial valuations.
Secondly, big data analysis has been able to help insurance companies detect claims that are fraudulent. These fraudulent claims are normally flagged before they are paid out.
When banners are digital, or they are placed on websites, it is data algorithms that control them. Different companies that have paid for spaces here are allocated different times during which they will appear. The advertiser is, therefore, able to control what rolls out, at what time and the duration without necessary being physically there thanks to the big data analysis.…