What is big data and what is it for?

Big data

Big data is the direction everyone is talking about, but few people know it well. E-commerce giants, industrial companies, and information corporations are investing billions in this technology. What is Big Data, what prospects do they offer and where are they used?

What is Big Data?

big data

Big data is a modern technological area related to the processing of large amounts of data that are constantly growing. Big Data is the information itself, the methods of its processing and analytics. The prospects that Big Data can bring are interesting to business, marketing, science and the state.
First of all, big data is still information. So large that it is difficult for her to operate using conventional software tools. It can be structured (processed), and unstructured (fragmented). Here are some examples of it:

• Data from seismological stations throughout the Earth.
• Facebook user account database.
• Geolocation information of all photos posted today on Instagram.
• Databases of mobile operators.

Big Data develops its own algorithms, software tools, and even machines. In order to come up with a means of processing constantly growing information, it is necessary to create new, innovative solutions. That is why big data has become a separate area in the technological field..

VVV – Signs of Big Data

big data

To reduce the fuzziness of Big Data definitions, features have been developed to which they must correspond. It all starts with the letter V, so the system is called VVV:

• Volume – volume. We measure the amount of information.

• Velocity – speed. The amount of information is not static – it is constantly increasing, and processing tools should take this into account.

• Variety – diversity. Information is not required to have one format. It may be unstructured, partially or fully structured..

To these three principles, with the development of the industry, additional V.s are added. For example, veracity – reliability, value – value or viability – vitality.

But the first three are enough for understanding: big data is measurable, incremental and heterogeneous.

What big data is for

big data

The main goal of working with big data is to curb them (analyze) and direct them. Mankind has learned to produce and extract huge amounts of information, but there are still problems with its management..


Right now, big data is helping to solve such problems:


• increase in labor productivity;
• accurate advertising and sales optimization;
• forecasting situations in domestic and global markets;
• improvement of goods and services;
• improvement of logistics;
• high-quality customer targeting in any business.

Big data makes services more convenient and profitable for both sellers and buyers. Enterprises can find out which products are more popular, how to form a pricing policy, when is the best time for sales, how to optimize production resources to make it more efficient. Due to this, customers receive the exact offer “without water”.

Source: lifehacker.ru 

Where more data is used

big data

• Cloud storage. Storing everything on local computers, disks, and servers is inconvenient and costly. Large cloud data centers become a reliable way to store information available at any time..

• Blockchain. The revolutionary technology that has been shaking the world in recent years simplifies transactions, makes them safer, and, most importantly, copes well with processing operations between a huge number of counterparties due to its mathematical algorithm.

• Self catering. Robotization and industrial automation reduce the cost of doing business and reduce the cost of goods or services.

• Artificial intelligence and deep learning. Imitating brain thinking helps make responsive systems effective in science and business..

These areas are created and progressed through data collection and analysis. Pioneers in the field of such developments are: search engines, mobile operators, online commerce giants, banks.


Big Data will be an integral part of Industry 4.0 and the Internet of Things, when complex systems from a huge number of devices work as a whole. Here are simple, no longer futuristic, examples of this:


• The automated plant itself changes the product line, focusing on the analysis of demand, supply, cost and market situation.

• Smart home gives recommendations on how to dress according to the weather and which route is the fastest to get to work in the morning.

• The company analyzes production and distribution channels taking into account changes in the real market situation.

• Road safety is enhanced by collecting data on driving style and violations of individual drivers, as well as the condition of their cars.

Who uses big data

big data

The industry’s greatest progress is in the US and Europe. Here are the largest foreign companies and departments that use Big Data:

• HSBC improves the security of plastic card customers. The company claims that it has 10 times improved recognition of fraudulent transactions and 3 times improved protection against fraud in general.

• Watson’s supercomputer, developed by IBM, analyzes financial transactions in real time. This allows you to reduce the frequency of false alarms of the security system by 50% and identify 15% more fraudulent activities..

• Procter&Gamble conducts market research using Big Data, more accurately predicting customer wishes and new product demand.

• The German Ministry of Labor achieves a targeted expenditure of funds by analyzing big data when processing applications for benefits. This helps send money to those who really need it (it turned out that 20% of benefits were paid inappropriately). The ministry claims Big Data tools cut costs by € 10 billion.


Among Russian companies it is worth noting the following:


• Yandex. This is a corporation that runs one of the most popular search engines and makes digital products for almost every area of ​​life. For Yandex, Big Data is not an innovation, but a duty dictated by one’s own needs. The company has algorithms for advertising targeting, traffic forecasting, search engine optimization, music recommendations, spam filtering.

• Megaphone. The telecommunications giant drew attention to big data about five years ago. Work on geoanalytics led to the creation of turnkey solutions for the analysis of passenger traffic. In this area, Megafon has a partnership with Russian Railways.

• Beeline. This mobile operator analyzes information arrays to combat spam and fraud, optimize the product line, predict customer problems. It is known that the corporation cooperates with banks – the operator helps anonymously evaluate the creditworthiness of subscribers.

• Sberbank. In the largest bank in Russia, super-arrays are analyzed to optimize costs, manage risk appropriately, combat fraud, and calculate bonuses and bonuses for employees. Similar tasks with Big Data are solved by competitors: Alfa Bank, VTB24, Tinkoff Bank, Gazprombank.

Both abroad and in Russia, organizations mainly use third-party developments, and do not create tools for Big Data themselves. In this area, the technologies Oracle, Teradata, SAS, Impala, Apache, Zettaset, IBM, Vowpal are popular.

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