The term Big Data is being progressively used almost everywhere. The term covers every single piece of data your organisation has amassed until this very moment. This includes data stored in the Cloud, social networking material from sites such as Facebook, Instagram, LinkedIn or Twitter, the URL’s you have bookmarked and on it goes. Your organisation may not even have digitized all the data as yet or your organization may not have structured all the data already. At this point, all the data, paper and paperless, structured and non-structured data within your organization is now Big Data.
Big Data works on the principle that the more you know about anything or any situation, the more reliably you can gain new insights and make predictions about what will happen in the future. By comparing more data points, relationships begin to emerge that were previously hidden, and these relationships enable us to learn and make smarter decisions. Most commonly, this is done through a process that involves building models, based on the data we can collect, and then running simulations, tweaking the value of data points each time and monitoring how it impacts our results. This process is automated – today’s advanced analytics technology will run millions of these simulations, tweaking all the possible variables until it finds a pattern that helps solve the problem it is working on.
Until relatively recently, data was limited to spreadsheets or databases, and it was all very ordered and neat. Anything that wasn’t easily organized into rows and columns was simply too difficult to work with and was ignored. Now though, advances in storage and analytics mean that we can capture, store and work with many different types of data. As a result, “data” can now mean anything from databases to photos, videos, sound recordings, written text and sensor data.
To make sense of all of this messy data, Big Data projects often use cutting-edge analytics involving artificial intelligence and machine learning. By teaching computers to identify what this data represents, through image recognition or natural language processing, for example - they can learn to spot patterns much more quickly and reliably than humans.
This ever-increasing stream of sensor information means we can now use data in ways that was not possible a few years ago. This is transforming the world of business virtually across every industry. Organizations are able to now accurately predict what specific segments of customers will want to buy, and when, to an incredibly accurate degree. And finally, Big Data is also aiding in running operations within organizations more efficiently.