Big Data is a new buzzword that many of you are probably familiar with. We have all heard it…but do we all actually know what it means? Could we all give a good definition?
Like many buzzwords, it is likely that not everyone can. But just in case you ever find yourself in a situation where you have to (for some odd reason) give a definition for Big Data, we have created an easy to understand, and easy to repeat definition.
Simple enough, right? Now let’s break this up piece-by-piece, to explain what exactly this means.
“Big Data is a lot of data…”
But when does just plain data become BIG enough to become big data? Data becomes “big data” when it becomes too big and difficult for a field engineer to analyze manually. Data is also big enough to be big data if it is big enough to not fit into one, single machine.
To learn more about the size of data and measurements of data, read here.
“…that is quickly generated…”
This is also referred to as “velocity” in the 4 V’s of Big Data. Because there are so many different sensors and devices that are constantly collecting data, we have loads of data being collected at any given time.
For example, check out the “Data in 1 Minute” section of this infographic on the Big Data Revolution. You can see that there is a great deal of data being collected in just one minute!
“…by a lot of different sources.”
This is the “variety” aspect of the 4 V’s. Because the data is being collected from many different sources, it comes in many different forms. We can collect data from sensors in devices, wearable devices, social media, excel files, email, mobile devices and more.
In general, we categorize these different “forms” of data into two types: unstructured and structured. To learn more about the difference, visit this site. Big data often contains a combination of both structured and unstructured data.