Big Data is everywhere these days. In this article, I will give you some awesome real-life Big Data examples to demonstrate the utility of big data.
Let me start this post off with what big data is...
Big Data is data that is too large or comes in at too high of a velocity to deal with using normal data systems like Relational Database Management Systems or RDBMs. You more than likely have heard of the three V's of Big Data which are increasingly are referred to as the four V's of Big Data:
It is a no-brainer that big data consists of data that is large in volume. Normally, we can consider data as big data if it is at least a terabyte in size.
Big data can arrive at high velocities like real-time data and have to be processed in near real-time.
Since we collect as much data as possible, this means that big data can be varied. It can be structured or unstructured data. Additionally, it can be video, pictures, audio, and sensor data. Big Data solutions need to be able to handle this variety.
Lastly, big data has to be of some value to your organization. In order to be of value we have to make sure that it is correct.
In this article, we will discuss some real-life big data examples of industries that make use of big data today. This should help you get a good idea of why big data is important today.
Checkout this video for more about what big data is:
Our first Big Data Example is the retail industry. Companies have always collected retail data like transaction history but now that we have big data we can pull in other types of data to help us make better-informed business decisions which increases profit.
Take for example social media. With big data, we can track social media discussions and shares about our products and services and perform big data analytics on that data. This could give us insights into the data that we have not been able to see before. We could identify the probability that a customer might have to switch to a competitor.
In addition, with big data, we can get better insights into our customers buying habits via loyalty program data.
