BIG DATA

Big Data : Definition, Challenges & Applications

The growing production of digital data and the arrival of solutions and tools for collecting, storing and analyzing them has become a big challenge for organizations from all sectors. But Big Data? Why is it so important to care about this? And what are the main issues?



What is Big Data?

Big Data Big Data is a global term defining very large data sets that can be analyzed by computer to reveal patterns, trends and associations, especially concerning human behavior and interactions. It corresponds to large quantities of digital data that are produced by businesses and individuals.

What makes these massive data so special is that they are very heterogeneous as they come from various sources: they can come for example from the use of computers, but also from mobile phones and tablets connected to the Internet: from searches on search engines, from textes, photos and videos posted on social networking, online shopping, etc. They also come from connected devices and sensors that are multiplying in all sectors: weather, traffic, surveillance, home automation, domestic consumption meters, etc.
See also: Big Data Definition

Another feature of these data is that they are very large. The widespread use of portable devices (computers, phones, tablets, watches) combined with the use of internet causes a dramatic increase in their volume. This significant volume of digital information requires the implementation of new technologies because the current systems are not prepared.
Voir aussi : Volume

Challenges

All these data are valuable information on the activity of users, customers or prospects of a company: internet browsing, search engines and publication of opinions on forums are indicators on the concerns and centers of interest of users, their habits, their requests, etc.
Within these large volumes of data, companies must be able to distinguish the most relevant information from those who have less interest or no interest at all. The analysis of these massive data becomes one of the major challenges to better understand the needs of people, analyze and anticipate consumer behavior, improve decision making, etc.
See also: Challenges

Applications





In the health sector, for example, massive data can help develop personalized preventive medicine. The arrival of an epidemic of measles, flu or another illness can thus be anticipated by analyzing keywords used in search engines.
In the transport sector, analysis of location data of travelers and vehicles allows the modeling of population displacement for example, and thus makes it possible to anticipate the necessary public facilities.
Big Data projects are multiplying in many other areas: education, sustainable development, marketing, trade, security, etc.
See also: Challenges