Big Data: what you need to know about the technology that has changed the world

tass.ru - September 29, 03:02

Where big data is collected and stored, why it is needed and how to apply it in business, we tell in the TASS material

How does the supermarket across the street know which products you have run out of at home, and why do they offer to buy them at a discount? How does a streaming service know you'll like a new series? The answer is through big data analytics. In recent years, there has been a real boom in this technology, and today many, even ordinary, processes are tied to it.

What is big data

Today, hardly anyone can be surprised by the fact that almost every Internet service guesses the user’s desires in a matter of seconds: it offers suitable products, films, music, and other types of content. Without big data analysis, this would not be possible. How exactly does it work?

Big Data is large data arrays that are processed using special automated tools and used to collect statistics, make or justify decisions, and make forecasts. In fact, this is a set of non-personalized data that together form an impersonal portrait of a user with a set of certain socio-demographic characteristics.

With the development of the Internet and information technology in general, data is accumulating more and more. The world's largest data operators - Google, Microsoft, IBM, Oracle, Amazon, and others - were the first to notice that they have the potential to be explored and put into practice. They began to actively collect user data, analyze it and use it to improve their own services.

Thus, the analysis of big data has opened up the opportunity for companies to analyze the habits of their customers and use the information received in the development of various development strategies. In addition, directions for studying Big Data began to appear in the largest universities of the world, and specialized specialists began to appear in the labor market.

Where and how is Big Data collected?

For big data to be useful, it must be collected and processed somewhere. The main sources of Big Data today are search engines, social networks, and blogs, as well as data from companies, especially in the areas of e-commerce, telecommunications, food tech, fintech, delivery, and taxi services, and streaming services. In addition, big data is formed using statistical data (medical, urban, meteorological, geographic, etc.), Internet of Things (IoT) data, and devices.

All this information is stored in data centers with the most powerful servers, which ensure its fast and high-quality processing. In addition to physical servers, cloud storage are often used - the so-called Data Lake ("data lakes"), as well as Hadoop and Spark platforms based on open source, created specifically for storing and processing Big Data. Thanks to the emergence of tools that greatly simplify the processing of Big Data and reduce the cost of their storage, analytics based on them has become even more in demand.

Big data use cases

The potential of big data analytics is so great that today it can be used in many scenarios and in almost all areas. Among the areas in which analytics based on big data is most often used today are industry, retail, medicine, and telecommunications.

In industry, big data analytics can predict accidents and optimize production. Having implemented a solution based on the "Internet of things", that is, "smart" sensors, at the enterprise, the company begins to collect data with which it monitors and analyzes the state of equipment, prevents possible failures, simulates production processes, studies their efficiency, and calculates the most economical models of resource consumption.

For example, "smart" sensors in nuclear or hydroelectric power plants monitor the operation of most systems in real-time, based on a variety of available data. When deviations from the norm are detected, the sensors are instantly triggered, allowing a person to react in time and troubleshoot.

The main value of using big data in production is cost optimization and cost reduction.

With the help of big data, a manufacturer can predict the demand for their products based on historical sales, seasonality of demand, market conditions, changes in the cost of consumables, etc. All this data is contained in a common database and gives an idea of everything that can affect production.

In retail, big data helps companies better understand their customers, optimize logistics, and more accurately predict sales.

Companies analyze consumer purchases, and identify patterns that allow you to more accurately calculate the demand for products. By adding information about the customers themselves, which retailers have, to this data, retailers make personalized offers to customers. And with the help of geoanalytics, retail companies make decisions about expanding to other regions and more accurately calculate supply chains.

For example, the implementation of big data analysis tools for the world's largest wholesale and retail chain Walmart has increased online sales revenue from 10% to 15%. Another example of the use of big data in this area is the improvement of the recommendation system. So, Amazon's new recommender system based on Big Data began to generate a third of the company's revenue.

The importance of using Big Data in medicine is due to the fact that almost every inhabitant of the Earth passes through the healthcare system, which means that data about him can complement the overall picture and help medical institutions work more efficiently.

For example, the analysis of big data makes it possible to investigate the effectiveness of the treatment and prevention of diseases. In addition, it allows the development of new methods of improving the health of the population, predicting the demand for medicines, and conducting mass screening in order to prevent epidemics.

Electronic health records are one of the main sources of real clinical practice data. Centralized collection of depersonalized medical records in "data lakes", information processing, its structuring, analysis, and study allows us to obtain a huge amount of valuable data necessary for solving various problems in the field of healthcare, for example, to assess the prevalence of diseases, conduct research, use data as evidence base.

Like retail in telecom, big data allows you to collect more detailed information about consumers and use it to improve service offers, develop new tariffs and services, predict sales, etc.

One of the most interesting and useful applications of big data in telecommunications is fraud prevention. Thanks to machine learning technology, operators are able to track spam calls and thus protect subscribers from intrusive advertising.

Telecom operators are one of the largest owners of big data, which allows them to offer Big Data analysis and processing services for companies from other areas. For example, MegaFon, as one of the leading telecommunications companies, has many years of experience working with Big Data. Thanks to partners, MegaFon's analytical tools analyze the data of 98% of the country's population.

Russian Big Data market

In Russia, today there is already a formed big data market, which is promised rapid growth. Thus, according to the Big Data Association (BDA) and the Boston Consulting Group, at the end of 2019, the volume of the Russian big data market was estimated at 45 billion rubles with a growth rate of 12% over the past five years.

In 2018, a profile association was created that brought together the largest players in the Big Data market in Russia, including MegaFon, Beeline, MTS, Sberbank, VK (formerly Mail.ru Group), Yandex, and others. The main goal of the association is to create conditions for the development of technologies and products in the field of big data in Russia.

The Russian big data market is still quite young, but its potential is huge. In 2019, the Association presented a strategy for the development of the big data market in our country. It contains proposals for improving market mechanisms and state regulation of the industry.

According to the calculations of the association, for the period from 2019 to 2024, the accumulated economic effect from the use of big data technologies can amount to almost 3 trillion rubles. The updated strategy for the development of the data market in Russia will be presented by the ADB at the end of 2022 - the beginning of 2023.

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