Big Data Is a Big Deal

 A lot of information about a lot of people – this is how big data can be described today. There is no industry where knowledge, forecasts and visions cannot be applied to your advantage. The world’s first known big data project, involving the administration of President Roosevelt, took place in 1937 in the US. 29 million records were analyzed. Sounds impressive? At the time, it was impossible to even imagine that by 2019, the world’s Internet traffic would be measured by billions of terabytes. The modern person is in a non-stop process of swiping, clicking, sharing and downloading. Interestingly, if we collect all the information that humanity has accumulated since the beginning of time up to the year 2000, it will come up to less than what we produce now in a single minute. By 2020, according to US analysts, one person will be producing 1.7 megabytes of new data. Strangely enough, only 0.5% of all world data is being analyzed, and only 5% of all data is somehow structured. As you can see, there is enough data for everyone.

Where does the data come from? There are three primary sources:

  • Social media data (events, promotions, tweets, comments, image and video downloads);
  • Machine data (information from sensors, industrial equipment, road cameras, GPS devices, satellites, medical devices);
  • Transaction data (offline and online transactions, invoices, payments, digital receipts, storage records). 

Big data for the retail industry provides a lot of advantages: first of all, it’s the understanding of who your business is intended for, what habits your buyers have, what they expect from the seller. Secondly, it’s an opportunity to find a new audience, to attract them and engage them in active communication. Aggregated data helps sellers understand their resources to optimize merchandising tactics, personalize their experience with loyalty programs, and provide timely consumer suggestions, including online advertising, offline targeting (remarketing), and more cross-sales.


For brands and retailers, data is an important indicator of changes, the model that controls the entire game. 62% of retailers agree that using data in business gives them a significant competitive advantage. In the business marketing strategy, big data makes it possible to develop a 3D model of the consumer (taking into account their preferences, needs and possibilities). The target audience can be narrowed down to the smallest details: location, hobbies, social status. Big data helps professionals optimize advertising campaigns in real time, improve customer engagement, and take advantage of delivering personalized, targeted advertising messages at the right time, place and context, monitor real-time marketing campaign performance and customer engagement levels.


The banking industry cannot function without big data either. The issues of primary importance here are reducing fraud and increasing customer security. Analytics can be very effectively used for security purposes. Previously, banks studied the credit history of individuals to analyze fraud risks, but now there is much more information to use: you can integrate complete customer profiles with their offline and online actions. Big data analytics can bring £322 billion to the UK economy by 2020, as well as improve retail banking. All this due to the ability to anticipate customer motivation and interact in a timely manner.


Modern education uses big data to control educational systems. Such systems allow teachers to create assignments and tests using information already available on the network with the help of automation processes. British teachers are integrating the Social Network Analysis & Pedagogical Practices (SNAPP) into the learning process by studying student blogs and measuring how interested they are in a particular course. Public resources such as YouTube, Google Scholar, LinkedIn, Social Science Research Network, online encyclopedias and forums are a virtually inexhaustible source of information for those studying or doing research. And with the help of big data analytics, you can identify the gaps still present in the field of virtual learning and fill them with relevant courses and modules.


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