Data specialists and analysts use regular software programs all the time- to examine data, clean it and perform more tasks on data sets. But these programs can only handle data sets that have a specific limit, they are not designed to deal with gigantic data sets. We all know that ever since the World Wide Web has come into existence and up till now, data growth has been spectacular and of course, it is only expected to increase even more in the coming years.
From 1986 till now, we have progressed from merely 2.8 exabytes of global data storage capacity to 1700 exabytes. So it's easy to think of big data as a huge collection of data, but what is it really about? A lot of organisations have data that increases on a daily basis. One such example would be that of social media. With millions of users generating millions of posts such as status updates, photos, links and so on, it only makes sense that social media websites have a huge collection of data to deal with.
However, you may come to ask the point in dealing with such a huge amount of data in the first place. Why can't we use sample data instead? Well, we are living in an age of information overflow, as well as an era where the digital world is booming. Especially in the wake of COVID-19, data on the Internet has increased more rapidly than expected.
Also See: Measures for Protecting Consumer Data #Infographic
Analysing large amounts of data can help businesses develop an in-depth understanding of what their consumers' needs and government organisations can better come to know the voice of the people. We get to hear the 'big data' term every day in our lives, and we come to understand it as the name suggests, but the infographic below shall sum up the hype of big data revolution for you.
Infographic by: Zenesys