From paper records that were widely used before the advent of computers, to spreadsheets and databases that were large collections of data maintained on computers, to the vast enormity of data that is generated and recorded today, the growth of data in the world has far outstripped human ability to maintain and make use of the data. Now it is that every two days as much data is created as was created from the beginning of time until the year 2000, and the pace of data creation continues to quicken. By the year 2020, the amount of digital information available will have reached 50 zettabytes, or 50 X 270 bytes. IT professionals attempting to enhance their knowledge and skill and their professional value are more and more looking to engage in a big data course of study.
There is essentially no human ability to process this quantity of data. No person could make sense of it, if any person would even try. Big Data computer programs make use of front line analytics that involve artificial intelligence and machine learning. By developing applications to analyze what the data represents, computers can learn to spot data alignments much more quickly and reliably than humans. Big data is used by various organizations, including those in government, education, and business. For business, the profit motive drives big data involvement.
1. Fraud Detection
Before the advent of big data screening, businesses processing any type of claims or transactions were saddled with enormous annual losses through fraudulent transactions. Processors were aware of the commonality of fraud and scanned for fraud, but generally fraud was detected only after the fact, by which point the damage was already done and only an attempt to minimize losses and prevent recurrence could be made. Fraud detection was not made and could not be made real time. Now, big data applications that can analyze claims and transactions in real time can greatly reduce the incidence of fraud, cutting operating costs and enhancing profitability.
2. Log analytics
IT departments generate huge quantities of logs and log data. Prior to the development of big data applications, most data was not examined because organizations did not have manpower or resources to process that information by hand. Within the list of big data uses, IT log analytics is among the most relevant.
3. Call center analytics
Call centers often provide a great measure of market attitude, but without big data analysis, much of the market perception that a call center can provide will be lost or discovered too late. With big data, problems with customers and staff behavior are detected in real time.
4. Social media analysis
A big data approach designed to analyze social media activity, can make sense of Facebook likes and Twitter tweets. Social media offers authentic discernment of how the market is reacting to products and advertising. With that information, companies can modify pricing and advertising for optimal results.
Big data is here to stay and marks the future for organizations of every type. For IT professionals, the big data course is also the wave of the future. The question can’t even be asked, how big big data will get. The question only can be, how will it be managed going forward?