Big Data is called Big Data when Data consists of the three Vs:  High Volume, High Velocity and High Variety. In other words, Big Data is so velominous, so varied and arrives at such velocity that it was formerly impossible to tackle it for analysis. Traditionally, Big data was called Big Data when It was too big to process correctly.

Now the term in used primarily in the context of Data Analytics,  User Behaviour Analyticsand Predicitive Analytics. 

With new data processing software, the dropping price of data storage, the formation of new data analysts being trained in high volume thanks to non-traditional classroom setting, we are now able to tackle data that we couldn’t before. New Vs have emerged in the last few years: Veracity and Value. The data needs to be true and the value is only discovered once it goes through a systematic process in order to discover it’s purpose to answer vital business or Scientific Questions.

How has databecome so big? Data is collected during any form of transaction that happens over a network: everytime you search on a browser or you make a phone call, everytime you use your credit card, or make any form of transaction (exchange of information from one software to another to create a link) over the internet even if it is just logging into Photoshop or taking a picture of your friend with a wireless device, you and the other party create some kind of data that is stored.

 According to Wikipedia, every day 2.5 exabytes (2.5×260 bytes) of data are generated.[12] Based on an IDC report prediction, the global data volume was predicted to grow exponentially from 4.4 zettabytes to 44 zettabytes between 2013 and 2020. By 2025, IDC predicts there will be 163 zettabytes of data.[13] According to IDC, global spending on big data and business analytics (BDA) solutions is estimated to reach $215.7 billion in 2021.

Relational database management systems and desktop statistical software are storing, organizing, processing and cleaning data, and eventually preparing data for analysis. Some of these relational databases are maintained and run  on thousands of servers.

Big data is used for analytical purposes, in order for business to streamline their profits by analyzing trends, predict user behaviour and make prediction.  It is also used extensively in healthcare in order to treat people better and to reduce cost.  Insurances create campaigns based on their data findings to prod people to a healthier lifestyle, also to reduce cost. In Science we use data within the Scientific Method to test and to prove scientific hypotheses. For example, during Covid we used data to see how the virus was evolving and infecting people within certain contexts of the population. We used data to see how to treat people and how to organize care. We also used data to make predictions and alert leaders to take certain precautions ahead of time.When Pharmaceuticals were creating vaccines, they used data to make vaccines and eventually  test them for safety.

Big Data is pivotal to making this world a better, world, to streamline products to avoid waste, and to find solutions to our problems. 

Data is the antigen to the so-called “Fake newsers” who make up correlations and causations, when there is none.Unfortunaly the very people who tell you to verify your information are the people who follow Presidents who claim boastfully they “Never read one book in their lives” and make stuff up as they go. Data doesn’t lie and the systematic processing of data makes it the most valuable asset if we use it and interpret it systematically.