The book Big data. A revolution that will transform how we live, work, and think by Victor Mayer-Schonberger and Kenneth Cukier tells about the importance of big data for the modern world, the prospects of using large amounts of information.
Data is no longer regarded as a static quantity that becomes useless when a certain goal is achieved. Now the data has become the raw material of the business, a vital economic contribution used to create new economic benefits.
The applications of big data may be different, but the result is one: the amount of data in the world is growing rapidly. Big data represents three steps to a new way of analyzing information that changes our understanding of society and its organization.
The first step is the quantity
In the world of big data, we can analyze a huge amount of data, and in some cases process all the data, and not rely on random samples. Sampling is a product of the era of limited information processing. The concept of sampling implies the ability to make the most of a minimum of materials.
Now, when we can put large amounts of data at our service, the samples have lost their importance. In many areas, there is a transition from collecting a small amount of data to as much as possible, and if possible, that’s all. The presence of a complete (or almost complete) data set gives much more freedom for research and a comprehensive review of data, as well as a more detailed study of their features.
The second step is accuracy
When the possibility of measurement is limited, only the most important indicators are counted, and the desire to get an accurate number is quite appropriate. Accuracy is suitable for small amounts of data.
But in the world of big data, strict accuracy is impossible and sometimes undesirable. When receiving huge amounts of data of a new type, in some cases it is possible to neglect accuracy if it is possible to predict the general trends. If we operate with data, most of which are constantly changing, absolute accuracy goes by the wayside.
The third step is causality
People are used to looking for reasons in everything, even if it is not so easy to trace them. In the big data world, on the other hand, we no longer have to cling to causality. Instead, we can find correlations between data that open up new invaluable knowledge.
Correlations can’t tell you exactly why an event is happening, but it warns of what kind. Correlations do not give definiteness, but only probability. Big data is based on correlation-based predictions. The practical application of forecasts will only expand over time. Correlations answer the question “what” and not “why”.
To show changes in general, we will use data-ization. Data-ization is not the same as digitization, in which analog information is converted into binary code read by a computer. It’s about converting everything on the planet, including what we’ve never considered information, into a data format through quantitative analysis.
Although the value of data has long been unquestionable before it was perceived as an addition to the main business or as rather limited categories of intellectual property and personal information. But in the era of big data, all data, without exception, will be considered valuable.
The value of data does not decrease as it is consumed. The data can be processed again and again. Data can be used by several people at the same time without compromising each other. Besides, unlike material goods, the information does not wear out as it is consumed.
But do not forget about the risks associated with big data. The Internet has made the tracking process simpler, cheaper and more practical. Because big data promises valuable insights to those who analyze it, it is natural to expect a rapid increase in the number of those who will collect, store and reuse your data.
There is also another danger to be noted: we risk becoming victims of the data dictatorship, as a result of which we will idolize the information and the output of the analyzes, and ultimately abuse it.
Society needs to balance the benefits of data reuse with the risks of disclosing it too widely. In this approach, the confidentiality of personal data is protected by the limitation of the time during which they can be stored and processed. Also, one of the innovative approaches includes the concept of differential confidentiality, which implies intentional blurring of data so that the request for a large data set does not give accurate results, but only approximate ones.
We cannot allow the uncontrolled development of big data when the formation of technology becomes beyond the control of man. It is necessary to promote the development of technology, not forgetting about the safety of people.
Big data is an important step of mankind in the constant desire to quantify and understand the world around us. What was previously impossible to measure, store, analyze and distribute finds expression in the form of data.
Big data is both a tool and a resource and is designed to inform rather than explain. It leads people to understand but can still confuse depending on how it is handled.
The book also focuses on the fact that big data will be useful in all areas of activity, including social, for example, in the treatment or prevention of outbreaks of mass diseases.
This book will be interesting not only to those who work in the field of IT but to all those who are not associated with this area, because the book affects the changes in the life of society on the whole.
Automatic Customer is a great example of how big data can be used in modern marketing.
