You have noticed that social networks offer to add friends with whom we have ever crossed paths, marketplaces recommend products that we will definitely pay attention to, and advertisements precisely adjust to our requests. All this became possible thanks to Big Data.
The science of big data and data engineering is used in almost all areas: medicine, business, banking, sports industry, industry, politics, marketing, etc. Big Data is the most important technological trend of recent times, which has radically changed the possibilities of using information.
In this article we will tell you why big data and data engineering is needed and how it helps companies reach a new level, and professionals earn more.
Volumetric arrays of structured and unstructured information are called Big Data, or big data. Any of our actions that have an information trail is only a particle in an endless array of data. Bank transactions, correspondence with friends, adding songs you like to playlists, orders in online stores, steps taken by the tracker – all this information is stored on the network and does not disappear anywhere.
Big data is accumulating at space speed. More than three million emails are sent every second – and these are just emails, without taking into account correspondence in instant messengers and social networks. In order to get a useful slice of information in the future, any data needs to be quickly processed and structured.
Big Data is a set of tools and methods for processing large and diverse amounts of data that people around the world generate every second.
Basic principles of Big Data
Quite often, Big Data is compared to a large database. In part, the comparison is correct, but with one amendment – the information in such a database must meet three criteria: volume, speed and variety.
Here’s what it means:
- Volume – big data includes those arrays of information whose volume of daily accumulation exceeds 150 GB per day;
- Update speed – big data is constantly generated and updated, and high technologies are required for its processing;
- Diversity – the accumulated data is always heterogeneous, they are of different formats, may contain errors, be structured or not structured.
Today, Big Data helps companies, corporations and entire institutions make strategically correct decisions. The main task of big data is to collect and interpret information as accurately as possible. Therefore, in addition to volume, speed and variety, two more factors are taken into account in modern systems:
- Volatility – big data can come with a certain frequency, during specific hours or seasons. Only strong processing technologies can manage bursts of unstructured data;
- Value – in order to competently structure large amounts of data, technologies are needed that will allow you to determine the degree of importance of incoming information.
How big data is collected and processed
Before any information can be obtained, data must be collected. There are three main sources of data collection:
- Social – these are social networks, sites, marketplaces, forums and any other Internet resources on which users perform any actions. Also, social sources should include statistics from different countries and cities: birth of children, registration of marriages, medical records, etc.;
- Machine – all information coming from smartphones, trackers, smart things, meteorological stations, satellites, etc.
- Transactional – such sources include bank transactions, money transfers and any interactions with ATMs.