Data. Humanity has generated them for millennia, literally from the moment of its inception. However, in those days, there was no question of any global arrays of unstructured information – the technical factor affected, people simply didn’t have such opportunities. In an era when not everyone knew how to read, there was no talk of any accumulation of colossal amounts of data. What do we have now? Internet, social networks, indicators of various measuring devices, various information related to the economy, business, etc. – this is only a small part of the sources of continuous data generation, which, in total, or individually, are able to reproduce their global volumes. It is logical that this phenomenon should have got some name. As a result, the term “Big Data” is firmly established in everyday life, which means “big data” in translation.
History of the term “Big Data”
It is not known exactly who first proposed the introduction of a separate concept for huge amounts of information, but its popularization and dissemination is largely due to Clifford Lynch, who served as editor in the journal Nature. In September 2008, under his leadership, a special issue of the publication was prepared, in which the main emphasis was placed on the issues of processing large amounts of data, the phenomenon of the rapid increase in their generation, the opportunities that open up for the scientific community if it is possible to learn how to benefit from them. It was assumed that the analysis of big data should undergo significant changes – quality, not quantity, would come first. Initially, the term “was intended” for use in the scientific community, but the main attention was paid, rather, not to the issues of directly studying the accumulating information, and the problems of explosive growth of its volumes and diversity. Nevertheless, the definition of bigdat quickly penetrated into other areas. In particular, already in 2009, the term often appeared in the business press, and a year later the first serious attempts were made in the field of solutions for processing global data arrays.
Big Data in current realities
The phrase Big Date is regularly flashed in the news bulletins and humanity has generally become accustomed to it. Although the overwhelming majority of people do not realize all the nuances, imagining it as a kind of repository with a huge amount of information that they somehow analyze, study, etc. That is, something hypothetically important, but not worth it to rack one’s brains over its features, since in everyday life there will be no use from this. Such a point of view has the right to life, but it cannot be called correct. Big date processing technologies are beginning to play an increasingly significant role, influencing the most diverse aspects of modern life, while simultaneously setting new serious tasks for humanity. For example, it is not enough to learn how to efficiently process such data arrays, it is equally important to ensure their reliable protection, security, etc. e. And here, companies often choose the wrong path: they begin to work actively with the bigdata, but practically do not deal with the creation of the corresponding infrastructure. Of course, this is difficult and costly, but it cannot serve as an excuse, because both the safety of information and its confidentiality, integrity, etc. are at stake. And here on the horizon there is another extremely promising and young technology – blockchain.
The attention of large companies
Before we consider how solutions based on a distributed registry will help in such a case as big data analysis, let us return to a few years ago. It was previously mentioned when the term “Big Data” appeared and in what environment it was originally used. If you explain it in very simple words, then this is information whose volume is so large that it is not possible to process it using classical methods.
A rapid increase in public interest in the big date is observed at the end of 2011. The evidence is Google Trends data, which show a sharp increase in the number of search queries for this term. As mentioned above, at that moment even the first solutions to work with such volumes of data already existed. Large players in the high-tech world did not stand aside: Microsoft, HP, Oracle, IBM and other well-known companies talked about the importance of Big Data.
Is Big Data something new?
Could it be that big data has been used before? Yes, but in marketing. There similar databases, filled with the most diverse information about customers, have existed for many years. For example, they may include arrays of data on people’s purchases, their lifestyle, etc. What is the use of this for companies? The ability to predict customer behavior in terms of needs, preferences and more.
What has changed now, since they started talking about it? The speed of data generation has increased rapidly. The foundation of the process was laid in 2002, when humanity entered the so-called digital era. Analog data began to lose ground, while digital volume showed unprecedented growth, increasing exponentially. According to experts, in seven years about 175 zettabytes of data will be accumulated, while in 2018 there were “only” 33 zettabytes. The bulk of information is generated by network users, the number of which is also growing. Moreover, it is predicted that by 2025, devices that belong to the category of the “Internet of things” will come first in this process. It is expected that such devices will generate about two-thirds of all information.
It is logical that the situation with the big date has changed, in particular:
- humanity has invented new ways of comparing and analyzing data arrays;
- Many new sources of information generation have appeared.
It is expected that in the near future, big date technologies will occupy an important place in such areas as healthcare, manufacturing, government, trade and more.
Note that perceiving Big Data purely in the context of certain specific arrays of information is somewhat wrong. A more accurate definition, rather, comes down to a set of methods by which they are processed.
Data sources
What data sources can be used for further analysis? Currently, there are plenty of them, so we will focus only on a few:
- internet of things;
- social network;
- information on the acquisition of goods;
- various GPS signals;
- meteorological data, etc.
The number of sources continues to increase. It is logical that methods for processing the accumulating information are being improved and developed.
How Big Data Works
In total, there are three principles of bigdat that define the requirements for solutions for their storage and analysis:
- horizontal scalability;
- locality;
- fault tolerance.
The first principle implies that the system should be capable not only of working with huge amounts of data, but also of dynamic expansion, since the size of information volumes can increase rapidly. The second indicates that it is more optimal to analyze the database on the same server where the latter is stored. This allows for significant resource savings. The third principle is as follows: the system should continue to function normally even in the event of failure of its individual components. And here we again come close to blockchain technologies that allow us to create solutions that meet the requirements of the above principles.
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What is Big Data for?
Where is Big Data already used today or can it be used effectively? In fact, the options are not so few. For example, take the field of medicine. If under normal conditions the doctor makes a diagnosis, focusing more on the medical history, examination results, symptoms, etc., then the involvement of large Bitcoin price prediction amounts of data in this area will provide a lot of different additional information, ranging from the experience of doctors who have examined similar cases to information how bad the environmental situation is in the patient’s area.
Another promising industry is unmanned vehicles. The creation of appropriate systems can be significantly accelerated, and the final solutions will be more effective if humanity uses “big data” in the process.
It’s hard to imagine modern trading without Big Data. How to sell a product to a potential buyer? To study his needs, habits, preferences in order to target an advertising campaign to a specific target audience. And where is the most similar information? In social networks, etc. At certain points, the big date analyst will even tell you the reason for opening a retail outlet in a particular area or settlement.
Large amounts of data came in handy for politicians. You don’t have to go far for examples, just remember the US elections when the unconditional, according to forecasts, leader Hillary Clinton lost to her opponent Donald Trump. This incident attracted the close attention of specialists who tried to establish the reason for the success of the candidate, who was predicted only the second place. In their opinion, the whole thing is the proper use of the advantages of the bigdat by the team of the then candidate for the highest position in the United States. Trump’s campaign headquarters approached the issue of working with voters radically different than it was accepted. Using a special mathematical model, a thorough analysis of the electorate’s data was carried out, which made it possible to target campaign materials, based not only on the geographic location of the voter, his gender or level of affluence, and considering factors such as intentions, behavioral characteristics, psychotype, interests, and more. In the end, almost every voter received his personalized message. Could he resist him?
Hypothetically, yes, but only if Hillary Clinton used a similar approach. Then the “battle” would be fought for every vote and the final result could be completely different. XRP price prediction In reality, her team decided to go the other way – the classic one. That is, the main emphasis was placed on the data of sociological research and standard marketing tools. Voters were divided into large conditionally homogeneous groups, for example, rich, poor, Hispanics, women, men, etc. As it turned out soon, such an approach was not true. In addition, it was also economically inexpedient: the election campaign cost Clinton almost $ 900 million, while Trump spent a little more than $ 400 million.
Big Data Challenges
Talking about the prospects of using big date, one should not forget about a number of difficulties that arise along this path. There are three key ones:
- determination of the importance of data;
- ethics of collecting personal information;
- storage safety.
The first problem logically follows from the features of Big Data: there is a lot of data, how to separate the “grain from the chaff” and understand what is really important? From the entire array, it is necessary to extract and save exactly the information that can bring one or another benefit in the process of their analysis.
The second challenge is ethical issues. Is it possible to use data at all, which, in fact, is not always obtained with the consent of the user. Even if they usually notify him of the collection of some statistics, the person himself may not be aware that he is sharing with Google not only the history of search queries, but also a bunch of other information. On the one hand, this allows companies to improve the quality of service, develop new, more convenient solutions, etc., and on the other hand, Big Data collects all the information that can be at least theoretically useful. As they say, what if?
All this personal information must be stored somewhere. Moreover, be kept in a safe and secure place. Processing solutions are also required to have similar qualities, which, in fairness, are not always ideal. And it’s also not so easy to find a good big date analyst in the state, as representatives of business circles complain. However, this does not stop large companies from investing in this industry, because it has a great future.
Big Data and Blockchain
So how can big date blockchain technology be useful? There are many options for their mutually beneficial use. Let us dwell on some of the most significant from the point of view of business representatives. First of all, this is access to various detailed information about consumers’ preferences, which will improve the quality of work with clients. Control will also increase – now it’s not a problem to track supply chains, to establish at what stage there were natural (for example, weight loss due to evaporation) losses, whether there were any fraud or attempted fraud, etc.
Talking about the prospects for introducing the blockchain will not surprise anyone. From a utopian idea declared by a small group of enthusiasts, it evolved to discussion at the highest level in financial institutions and world-class companies such as Visa, Citibank, etc. Here it is appropriate to quote Oliver Bussmann, who occupies one of the leading posts in the financial holding UBS, who is confident that using distributed registry technologies it will be possible to drastically reduce transaction time – operations will take literally several minutes, not days, as in current realities.
The synergy of blockchain and bigdate technology also looks very attractive from the perspective of obtaining all kinds of financial information. The first component of the conditional system guarantees the safety, transparency and integrity of information, while the “big data” will provide it with a vast number of new effective tools for analysis, modeling, forecasting, etc. As a result, management decisions will be more balanced and based on information, the reliability of which is much higher.
The above was an example of Big Data in healthcare. Is it possible to organically add blockchain technologies there? Of course. This is beneficial for both the doctor and the patient. The first receives the most complete information about the patient, which simplifies the diagnosis, the second – effective treatment. At the same time, information about patients is reliably protected, somehow changing them, making adjustments, etc. will fail. Along the way, medical institutions could exchange relevant data about patients, providing them, for example, to scientific organizations, insurance companies, etc.
Array data security and blockchain technology
Requirements for decisions in the field of big data necessarily imply fault tolerance, ensuring the integrity of information, protecting data from attacks by third parties, etc. Integration with blockchain technologies will help to cope with the above challenges with maximum efficiency. Take the same fault tolerance, which implies that the system continues to function correctly even in the event of a breakdown of individual components. The main feature of the blockchain is the distributed registry. There is simply no single center. Therefore, it cannot be disabled. A network consists of a large number of independent nodes and gaining full control over one or more will not produce any result. Yes, you can try to somehow distort the data by using the access right, but the network will reject them and will not consider them reliable. It turns out that not only the safety of arrays of information is guaranteed, but also their immutability. Blockchain-based solutions will allow you to effectively analyze big date data, establish communication with other institutions or systems, provide convenient information exchange functionality, and guarantee confidence in information.
In one of the well-known expressions, it is stated that the world is owned by one who has the relevant information. It is difficult to disagree with this, because the value of relevant information is so high that sometimes it decides the fate of entire states, and not its individual citizens. Information confidently evolved from ordinary data into a valuable asset. Therefore, it is necessary to take care of its safety. Financial institutions, companies, etc. in any case, they will not be able to function successfully, having fenced off from the world and ignoring the opportunities that modern technologies of data collection and analysis provide. And here Big Data in combination with blockchain technologies will be very useful, because in combination they have a number of unique and extremely important properties. The only thing left is their integration.
