All You Need to Know About “Big Data”

It is not a secret to anyone that global data volumes are growing exponentially. All this information must be stored somewhere, somehow processed, and also be useful. In recent years, a new term “Big Data” began to appear in the media very often. Almost all active Internet users have heard about it, but few have an idea of what it is and how it works. In this article, we will tell you in simple words about all the nuances of this technology.

What is Big Data?

If not to go deep into complex terms, then Big Data is a variety of tools and methods for processing a large amount of information, both structured and unstructured.

Unstructured information is data that is not organized in a specific order or does not have a certain structure.

This term was first introduced by editor of the magazine Nature, Clifford Lynch relatively recently, namely in 2008. Of course, mankind stored and processed a large amount of data long before the introduction of this term. A stream of information that exceeds 100 GB per day can be called “Big Data”.

Let’s find out how Big Data works on a simple and illustrative example. Imagine a hypermarket in which all products are not in their proper places: fruit is next to baked goods, ice cream is near alcoholic beverages, tooth groceries – opposite a rack with newspapers, on which, among other things, there are mango, tofu, and salmon. In this case, Big Data helps to arrange everything on familiar places and helps visitors find a certain food product, find out its price, shelf life, how many people buy this product, etc.

So, as you already understood, people process a large amount of data for their subsequent effective use.

What are the ways to analyze data?

  • Data Mining;
  • horizontal scalability;
  • crowdsourcing;
  • statistical analysis;
  • artificial neural networks;
  • spatial analysis;
  • data mixing and integration;
  • machine learning;
  • visualization of analytical data;
  • forecast analytics;
  • simulation modeling;
  • pattern recognition.

The main technologies for analyzing a large amount of information:

  • Hadoop;
  • MapReduce;
  • Hardware solutions;
  • NoSQL.

Back in 2001, the Meta Group company identified the main characteristics of Big Data, which are called “Three V”:

  • Volume – is the total amount of data.
  • Velocity – how fast the new information is growing.
  • Variety – the physical ability to simultaneously process different types of data.

How to use Big Data in practice?

It is worth noting that large amounts of diverse and rapidly entering digital information are not physically possible to process quickly and qualitatively using traditional tools. That is, it is impossible to gradually process data step by step, it is necessary to analyze the whole array at once. Directly the analysis of information itself allows seeing certain patterns that are imperceptible at first glance. This allows improving all spheres of human activity, from production to government administration.

Big Data in numbers

Let’s turn to the official figures in order to realize the real volumes of accumulated data, and most importantly the rate of their growth. So, according to IBS company, in 2003 the number of world data was 5 Eb (1 Eb = 1 billion gigabytes). After 5 years, in 2008 this figure was 0.18 ZB (1 ZB = 1024 exabytes), in 2011 – 1.76 ZB, in 2013 – 4.4 ZB, in 2015 – 6.5 ZB. According to forecasts, in 2020 the volume of accumulated data will be about 44 ZB. And every year, their number will grow exponentially.

The largest banks of the world actively use the analysis of a large amount of data in order to:

  • manage risk;
  • provide quality service to its customers;
  • optimize costs;
  • fight against scammers;
  • segment and evaluate the paying capacity of its customers;
  • manage staff more effectively;
  • predict and prevent queues in the branches;
  • count employee bonuses;
  • generate financial statements;
  • analyze reviews in social networks;
  • manage customer churn, etc.

Big Data in marketing

With the help of Big Data, marketers not only made their work easier but also got the opportunity to predict its result in advance. For example, through Big Data, it is possible to display certain advertisements only to potentially interested customers. All this was made possible thanks to the RTB-auction model. Analyzing Big Data helps marketers get to know the end users better and attract far more interested customers.

For example, the popular Google Trends service helps to make a forecast of the seasonal activity of demand for a particular product or service.

Big Data in business

Everyone who deals with Big Data can be divided into several groups:

  • Infrastructure providers. They deal with the storage and pre-processing of information (Oracle, IBM, Microsoft, etc.).
  • Data mining. They systematize and help to extract the necessary information to customers (Glowbyte Consulting, Yandex Data Factory, CleverData, etc.).
  • End users. Organizations that acquire ready-made software and hardware systems for analyzing large amounts of data. As a rule, these are financial, retail and telecommunication companies.
  • Integrators. They provide services of direct implementation of analysis systems for end users.
  • Developers of full services. They provide turnkey solutions in this area.

The largest companies around the world actively use the analysis of large amounts of data to optimize costs and improve the quality of the goods or services provided. For example, PJSC Magnitogorsk Iron and Steel Works, one of the world’s largest steel producers, integrated Big Data to optimize expenses. At the end of 2016, they launched a service called “Sniper”, with its help, the specialists of the plant achieved a reduction in the cost of ferroalloys, as well as other materials in the production process. “Sniper” processes a huge array of data, and then makes recommendations that help to significantly save money.

Conclusion

Big Data technology is rapidly integrating into almost all spheres of human activity. The amount of accumulated data will only grow every year, and besides, exponentially. It is still difficult to say, how fast Big Data will “capture the planet”, but the fact that this will definitely happen is no doubt.

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