Big Data Personified…
Introduction
So what precisely does the term — ‘Big Data’ — refer to? And why is it such a pressing — and popular — concept within the Data Science community?
One of the definitions of big data is that it is a large repository of unstructured information that contains an assortment of data types, and it continuously expands in size over time.
Put succinctly, big data is a large and complex data set, originating from multiple data sources. Furthermore, these data sets are so voluminous that traditional data processing software quite simply cannot handle them.
Where did the term — ‘Big Data’ — Originate from?
Big data comes from the concept of data mining which originated many years ago. Although the notion of big data itself is somewhat new, the origins of large data sets go back to the 1970s, when the world of data and information was merely commencing.
Then around 2005, IT professionals began to discover just how much data users spawned through social media sites like Youtube, Facebook, Twitter, and other similar online services. Hadoop, which is an open-source framework designed specifically to store and study big data sets, was developed that very same year.
How can one source Big Data?
Big data can be gathered from publicly shared social network sites, and open forum website comments, and sometimes voluntarily gathered from personal electronics and apps, through questionnaires, product acquisitions, and digital check-ins. Additionally, the presence of sensors and other inputs in smart devices allows for data to be gathered across a broad spectrum of conditions and occurrences.
Big data is stored in large computer databases and is analyzed using software specifically designed to handle large, complex data sets.
What’s in Store for Big Data in the Short-Term?
While big data has come so far in such a small period of time, its effectiveness is just commencing. Cloud computing has expanded big data opportunities even further. For example, the cloud offers truly elastic scalability, where data carvers can simply spin up powerful clusters to test a subset of data. And visual digital graph databases are becoming increasingly important too, with their ability to display enormous amounts of data in a way that makes data analytics swift and extensive.
Nearly every department within any company can employ findings from data analysis — from marketing, to human resources and technology to sales. Big data aims to increase the speed at which products are commissioned to market, reduce the time and resources required to gain market adoption, target segmented audiences, and ensure customers stay satisfied.
Recap and Wrap-Up
Big data is an enormously large volume of data and datasets that arrive in diverse forms and multiple sources. As a result, many institutions have identified the advantages of collecting as much data as possible. Though it is not enough to simply accumulate and keep big data — you have to make it useful. By adopting rapidly growing technologies, organizations can use big data analytics to convert petabytes of data into actionable business knowledge and insight.
