What is Big Data - a definition
Considered the final stage of the third industrial revolution, Big Data is vitally important in today's world. But it can be confusing for the uninitiated. To say that big data is the sum of all the data generated on the internet and managed by companies does not tell the whole story. We need to go a little deeper to define and understand big data.
Contents:
- Definition of Big Data
- Big Data: the 3 Vs
- IoT’s role in Big Data
- The benefits of Big Data for companies
Definition of Big Data
By definition, big data is a “field of technology dedicated to the analysis of huge volumes of computer data”. We can add that the data collected is measured in zettabytes: in 2020, some 64 zettabytes (that’s 64 billion terabytes) were generated and a volume of 180 zettabytes is already being predicted for 2025. This vast accumulation of information comes from all the software, applications and objects that are connected to the internet.
More prosaically, big data is all the data inherent to internet uses: searches, watching video, posts on social networks, online shopping, use of connected objects like routers and smart watches, GPS data, etc. This data is for the most part stored in Data Centres spread all over the world. It is mostly the big names in web services and computing that generate, hold and manage big data.
Since big data is a very large-scale phenomenon, it is also complex and takes several forms. The precise definition of big data can therefore change depending on the interested parties.
Big Data: the 3 Vs
There’s another definition of big data we can call on, popularised in 2001 by Gartner, the leading US consultancy renowned for its research into advanced technologies. By this definition, big data is high-volume, high-velocity and high-variety information assets. These are the 3 Vs of big data:
. Volume. Big data is high volume in two ways. There are many data sets, and the data sets themselves are massive and unstructured. They are growing every day, and new data is constantly being added. New storage systems are being introduced year-round to store ever more data.
. Variety. Another defining characteristic of big data is the variety of the data. It comes from different places and in various formats. The growing number of objects connected to the internet (IoT) and cloud computing provide more material for the databases. What we generate is encouraging companies to use ever more sophisticated processing tools.
. Velocity. The volume and variety of data processed require ever more velocity for managing massive data sets. Where previously the processing took place after the fact, using relational databases, the current trend is to respond to user needs as quickly as possible, even in real time, thanks in particular to NoSQL.
Two more Vs can be added to these first three: value and veracity. Each data point has its value, which can vary according to the use found for it. More and more companies are following the lead of the big web players, by earning money from the data they collect. And the value of the data depends directly on its veracity, its reliability.
IoT’s role in Big Data
IoT’s role in Big Data
The Internet of Things, or IoT, is the set of internet-connected objects and technologies that use the web and other communication networks to transfer data. Any object with a sensor and a communication unit is a part of it. These objects have a major role in big data, and the proliferation of internet-connected items is exponential: around 10 billion connected devices in 2020, with most analysts predicting over 50 billion for 2025.
These connected objects generate use data to add to the other traditional sources of data, such as online shopping.
This exponential growth in big data is also exacerbated by the use of cloud computing. This big data technology enables companies to store and manage their data on external equipment. It’s a type of IT use that helps companies, which no longer need to invest in hardware that is expensive to acquire and maintain.
The benefits of Big Data for companies
. Improving the customer experience, or UX (User Experience). By pulling together data from different sources, we can offer services with significantly improved quality. Streaming platforms, for instance, can suggest relevant material based on your viewing history. So big data is very useful for marketing departments.
. Fraud detection and compliance failures. Information aggregated by big data can be used to uncover abnormal behaviours that are symptomatic of hacks and frauds.
. Inputs for machine learning and deep learning. Big data technology is part of the artificial intelligence picture, mimicking neural networks. It can be used for image recognition and to help voice assistants understand natural language.
. Tracking markets in real time to offer the most appropriate prices and monitor competitor activities.
. Developing solutions and projects according to the real needs of the market, thanks to the suite of technologies used for big data: cloud computing, machine learning, etc.
See also:
. What are the major challenges for Big Data?
. What is the difference between NFC and RFID?