Big Data, we hear a lot about it these days but how many of us know what it means? If you too are lost when we approach the subject, here is a little catch-up course!
What is Big Data?
Data is an English word that means data, so far so good! When we talk about Big Data, the data in question represents all the computer traces that we leave behind us daily. Indeed, by moving from the industrial era to the information age, we have seen our data become dematerialized, from emails to bank cards and other connected objects, we are constantly sowing information online like a modern-day Tom Thumb.
This phenomenon is growing every day with the explosion of dematerialized data, a figure that is expected to double every 18 to 24 months. To give you an idea of ​​the volume that this represents, from 2011 to 2013, more data was produced than in the entire history of humanity. Our data has always been analyzed by marketing and advertising, but with the emergence of the Internet, their volume has become so large that it is a real business, which we call “Big Data”, the latter leading to the multiplication of tools to store and process this data.
The three pillars of the definition of Big Data are the 3 Vs:
- A very high volume of data
- A very large variety of data
- Processing speed that is similar to real-time
Concretely, what is Big Data used for?
After storage, the data must be stored and sorted, this is data analysis. From there, we will be able to use them to create better access to data with, for example, directories, new data with statistical sites, or even predictions from data analysis such as weather forecasts.
For the business world, this is a major revolution. It is a paradigm shift, the organization will now be guided by data. Indeed, this data represents more than an economic boon for those who know how to decipher it, it is now at the heart of the strategic process of companies to create added value. The implementation of data-related tools makes it possible to fulfill several missions:
- Refine the customer experience with data directly corresponding to the target audience
- Adapt the marketing strategy to a specific target and therefore increase its performance
- Evaluate and strengthen the company’s business model based on the feedback collected
What are the challenges of Big Data?
In 2014, the global turnover of this sector was estimated at 30 billion dollars, an increase of 66% in one year, according to a study by Research and Market, and a turnover of 50 billion is expected in 2018. Big Data still has a bright future ahead of it, but what does this imply?
First of all, in terms of employment, Gartner predicts 4.4 million additional jobs by the end of 2015 thanks to the development of data processing in companies, including 137,000 in France by 2020. The growing quantity of data will go hand in hand with spending on Big Data, which will increase by 30% over the next 5 years.
It would be very positive if the heated debate between pro-data and those who refuse to have their data exploited was not raging. If Big Data can make our lives easier with applications such as the connected refrigerator capable of alerting us when a product is reaching its expiry date, it also leads to data monetization and relentless computer tracking. Most free websites use their users’ data to make money by offering them for sale, which involves increasingly persistent and personalized advertisements that appear in our browsers.
On the one hand, Big Data is used to create tools that revolutionize our lives with medical research or various applications that simplify our lives, particularly in transport. On the other hand, there is the other side of the coin and abusive advertising practices that lead to abuses such as computer data theft.
