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Big Data, or Big Data, is called the new oil because it brings fabulous profits. BizUPLab kft specialists shared in simple words what Big Data is. By the way, this is one of the areas of work of our company.

Big Data is huge amounts of information that is first collected, structured, then analysed and used to make decisions or forecasts. For example, an online shop collects data about customers and their orders in order to form the right assortment and show advertising to those who will be interested in it. Based on customer behaviour, experts see when demand is higher, such as before holidays, and predict how much to increase the stock of goods.
The term Big Data was first used in 2008 in an article by American scientist Clifford Lynch published in the journal Nature. In 6 years after the term appeared, Big Data began to be actively collected and used by such corporations as Google, Microsoft, Apple, Facebook. Now Big Data is used by almost all large companies and government agencies.

Big Data in simple terms

At first, the main characteristics of Big Data included the three V's:
  • volume - materials occupy terabytes and petabytes of storage;
  • velocity - data is rapidly generated and constantly updated in real time;
  • variety - big data can exist in any form: animations, films, transactions, audio files, sensor readings, tables, text files, etc.

Over time, three more V's have been added:
  • veracity - given that management decisions are made based on data, the information must be from reliable sources;
  • variability - the acquisition of information is characterised by dips and spikes in activity;
  • value - obviously, billionaires' bank card numbers and pin numbers are more valuable than their tweets.

The main sources of data are:
  • user profiles on websites and social networks;
  • customer data of companies (orders, payments in online shops, additions to basket, etc.);
  • official statistics (birth rate, mortality, migration, education level, etc.);
  • readings of devices (readers, sensors, trackers, etc.)
  • media;
  • scientific discoveries, medical research;
  • data from satellites and measuring devices;
  • internet.

All of this is stored on servers, in cloud storage and in so-called data lakes. To process the huge amount of information, state-of-the-art tools, including artificial intelligence, are used.

Characteristics

BizUPLab Hungary specialists have listed the main methods of analysing Big Data.
  1. Classification: Grouping new data according to the principles that were previously applied to similar data. For example, if a new object breathes, walks, growls and barks, it is most likely a dog.
  2. Cluster analysis: finding common features and grouping according to those features
  3. Data mixing and combining. Information from disparate sources is combined to reveal a pattern. For example, phone records, transcripts, interrogations show whether a person has committed a crime.
  4. Machine Learning. Artificial intelligence itself looks for solutions to a problem by analogy with similar problems it has solved earlier.

There are many methods of analysing big data, said the managers of BizUPLab IT company. In general, they can be divided into two main categories Both categories are equally necessary and important in Big Data analytics:
  • Descriptive: something has already happened and we are trying to understand what exactly and why.
  • Predictive: something is likely to happen in a certain way because similar things have happened before.

Despite the high cost of hardware, software and skilled personnel, Big Data is now a major tool in decision making for large networked businesses, government agencies and international organisations.

Methods of analysis

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