The human mind cannot even imagine the amount of data that, for example, a small group of users exchanges on a daily basis on the internet. Computers can handle this, but even in this field, the situation has become so complex over time that it was essential to look for new ways of perceiving and analyzing the floating data so that their collection and arranging could be useful.
Over the years, you may have come across a term called Big Data more and more often used to denote a process that involves discovery, allocation, storing, analyzing and presenting a countless amount of digital data.
Although it is a process that has only been studied for a few years, the concept of “large data sets” was defined in 1997 when the term was mentioned in a scientific article published by the Association for Computing Machinery.
Even beyond our awareness and control of all the processes that form Big Data, all our activities make them an integral part of everything we are, everything we have, and everything we do, becoming an integral part of our lives, collecting and sorting details about our habits, decisions, style, groups we belong, the situation we live in, by constantly analyzing such data in order to increase efficiency and develop new products so that people similar to us prefer If over other goods.
Big Data consists of various data, the volume of which is constantly increasing at an ever-increasing rate. The whole concept originated in the 1960s when the first data warehouses began to be built. Data storage today is being supported by processes that cost significantly less than those a few years ago, which makes their collection, sorting, and storage even more beneficial.
Collecting Big Data
Collecting data in this way is useful for many entities – companies, clients, advertisers, or all those who want in any way to get the most reliable information about the market, competition, customer habits, price adjustment, and countless other details that are possible to be found out this way.
This way of obtaining specific data is much more practical than conducting research or surveying those who should be involved in a process. For example, the fact that a buyer who belongs to a certain age group, class, who lives in a certain place and has certain habits chooses one particular product is much more useful than the one that would be obtained through some research.
If you were to ask a group of people a question about their choice as they shop, it is very possible that the answer would not correspond to the choice they actually make, because answering a survey is influenced by psychological factors, so the results do not reflect reality. In addition to that, it would be almost impossible to constantly monitor all processes in order to obtain comprehensive answers to all the questions that need to be asked.
Numerous systems within everything we use are “in charge” of transmitting and collecting data, and information about it can be stored for reuse, or just once.
Big Data makes an endless array of details about an entity collected in a variety of ways to use electronic devices, which can include websites that someone visits, apps they have on their phone, email addresses they communicate with, phone numbers they talk to or send messages, but also smaller systems such as, for example, any home smart device, such as thermostats, alarms, GPS devices, exercise equipment, smart vacuum cleaners, smart refrigerators or washing machines and many other devices that can be controlled via mobile apps.
In this sense, Big Data refers to an extremely large set of data that no conventional database or information management tool can process. This type of data was first collected in a comprehensive way by internet giants such as Google, Yahoo, and Facebook, and then by many other companies even outside the ICT market.
Just as the amount of data that encompasses all of this is unimaginable, it is impossible to imagine the number of potential uses of these data.
Holding this amount of data is useful in countless ways because figures consist of large and complex data sets, collected separately from new sources. These data sets are so large that traditional data processing software encounters obstacles to manage them, creating a new set of tools and software.
Big Data includes data that may or may not be structured. Structured data have a fixed, usually digital format and in most cases are processed with the help of devices, and not with the help of a process that involves human activities. This type of data consists of information that a particular entity already manages within its own databases.
Big Data includes data that may or may not be structured. Structured data have a fixed, usually digital format and in most cases is processed with the help of devices, and not with the help of a process that requires a human engagement. This type of data consists of information that a particular entity already manages within its own databases.
On the other hand, unstructured data are information that is not organized and does not have a encoded format, because it can refer to almost anything, such as those collected from users of social networks or certain services on the internet and can be placed in existing files.
Data may also be semi-structured, i.e. they may contain both types of data, such as internet server logs and data from a sensor. Although not classified, they may contain basic information or tags that separate different data elements.
Despite the fact that it seems as if certain factors and processes appear on their own, Big Data, at least for now, cannot fully function, nor does it make sense to exist outside of human intelligence.
Despite the fact that activities in the development of artificial intelligence are very intensive, while AI is closely related to these processes, the human mind and its analytical skills are still necessary, especially when working on improving this area.
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