Big Data — Definition, 4V’s and its Application in MNCs

What is Big Data?

Big Data refers to the large volume of data — both structured and unstructured — that grows at an ever-increasing rate.

Big Data doesn’t only relate to the large volume of data. But how the data is processed by the company or the organisation matters more and the time taken in that processing.

Big data often includes data with sizes that exceed the capacity of traditional software to process within an acceptable time and value.

4 V’s of Big Data

1. Volume of Big Data

The volume of data refers to the size of the data sets that need to be analyzed and processed, which are now frequently larger than terabytes and petabytes.

2. Velocity of Big Data

Velocity refers to the speed with which data is generated. High-velocity data is generated with such a pace that it requires distinct (distributed) processing techniques. For instance, FaceBook processes 500+ Terrabytes of data each day.

3. Variety of Big Data

Generally, Big Data comes in three types namely — Structured, semi-structured and unstructured data.

4. Veracity of Big Data

Veracity refers to the quality of the data that is being analyzed.

How MNCs use BigData?

1. Google

Google actually has a large amount of data and a set of tools for working with it. It has evolved from an index of web pages to a central hub for real-time data feeds on just about anything that can be measured. Big Data analytics which means using tools designed to sort through and make sense of this data comes into play whenever we carry out a search. The Google algorithms run complex algorithms designed to match the query you entered with all the data available. It will try to determine whether you are looking for news, facts, people or statistics, and pull the data from the appropriate feed.

2. Facebook

The main thing Facebook does is to understand who their user is, by understanding their user’s behaviours, interests and their geographic locations. Giving us increasingly convenient ways to keep in touch with friends and family has proven to be a huge draw and made Facebook one of the biggest companies in the world in a little over ten years. It also means they have collected a lot of data on us, and we can use this Big Data ourselves. It comes into play when we search for old friends, by matching our search results to people we are most likely to be connected to. Advanced technologies pioneered by Facebook include image recognition a Big Data technology which teaches machines to identify the subject or details in a picture or video, by training it with millions of other images. This is what allows it to recognise people in pictures before we tell them who they are when it suggests friends to tag. It’s also why, if it discovers we like looking at, for example, baby or cat pictures, we will see more pictures of those things in our feed, when our friends share or “like” them.

3. Amazon

As the world’s largest online store, Amazon is also one of the world’s largest data-driven organizations. The differences between Amazon and the other internet giants mentioned here are largely down to marketing. Like Google and Facebook, Amazon offers a wide range of online services including information search and advertising, however, its brand is built on the service it first became famous for shopping. Amazon compares products we browse and buy with millions of other customers around the world. By building a profile of our habits, it is able to match us with products and recommendations from others which will most likely fit our needs. The Big Data tech at work here is known as a recommendation engine and Amazon’s was one of the first, and most sophisticated. As well as shopping, Amazon lets us take advantage of its platform to make money ourselves. Anyone who sets up as a trader on their platform benefits from the data-driven recommendations which will, in theory, drive suitable customers towards their listings.