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Big Data is one of the key digitalization tools. Their use in public administration and business began at the turn of 2010. But the relevance and possibilities of using this technology only increase with time. The reason is that the amount of information generated by humanity is growing rapidly. And for its effective use, an increasing number of users have to connect to the analysis and processing of Big Data.
The classic tool for working with large amounts of information – structured databases – cannot process such volumes of information. This was the main reason for the emergence of Big Data technology. This term refers to working with a large amount of loosely structured, stored in different formats, and frequently updated information. Big Data may include text documents, video and audio recordings, program code, geolocation data, etc.
An important component of working with Big Data is the technology of their collection: not only internal data is used, but also information search on the Internet, social networks, etc. Considering that “Big Data” is constantly updated, the efficiency of analysis algorithms and the ability to obtain results online. One of the most promising tools for working with Big Data is neural networks. In this article, we will present to you the top 5 reasons why you should really use Big Data.
1. Speed Of Processing And Decision Making
IBM claims that around the world, enterprises generate almost 2.5 quintillion bytes of information every day! 90% of the total array was received only in the last 2 years. And modern technology allows you to super-fast process these unthinkable arrays of data – literally in milliseconds! Back in 2016, Mercedes-Benz proved the possibility of organizing successful unmanned transportation. So unmanned trucks drove in a column of 600 kilometers – from Stuttgart (Germany) to Rotterdam (Netherlands). It would seem, what do Big Data services have to do with it? The fact is that without constant analysis of the environment and the situation on the road, cars would not be able to make such a successful trip. For comparison: the speed of a person’s reaction to a difficult traffic situation is 1.4 seconds, and the speed of the system is 0.1 seconds.
2. A Solid Base For Business Decisions
For example, how to understand that the network of establishments can be expanded to a particular area? At a minimum, analyze the relevant share of addresses that order food from the company. If the purchasing power of these visitors and demand is at the level we need, we can build on this data and make a decision. The basis is only facts and figures, so it is very difficult to make a mistake here. It is clear that the analysis of global, local, and indirect competitors, as well as their advantages, also significantly affects the overall picture, but this is more a matter of business analysis and marketing strategy.
3. Efficiency Of Results
Now marketers can not only accurately determine which target audience to target but also influence potential buyers exactly when they are able to respond. Thus, it is easier to attract customers, profits are multiplied, and the costs of involving mechanics are steadily decreasing.
Regarding the client himself, the system finds the best-personalized offer for him, which is more likely to be accepted immediately. A striking example is any contextual advertising that you have ever seen. The company analyzes the behavior of its potential customers on the site and forms individual offers based on their interests. This is what all major retailers do.
4. Revealing Patterns
The complexity of processing Big Data by the human brain lies not only in the fact that there is obviously a lot of data, but also in the fact that they are absolutely not structured and are stored randomly in tables, charts, images and other forms. All this complicates the search for useful patterns that allow us to identify causal relationships at the global level.
For example, a thorough content analysis of a particular publication (or a group of them) can clearly show not only the agenda. It also can display the editorial policy of the media, the quality of their influence on the masses and the political elite, and, as a result, on world events. The ability to keep track of such things provides a good basis for forecasting and analytical activities.
5. Understandable Metrics
Working with large data arrays allows answering a number of difficult questions – why the course of the event is exactly like this and what kind of forecast can be made right now. In the past, a whole team of experts answered these questions (and, by the way, spent a lot of time on this), but the human factor always led to errors. Automatic analysis of information excludes these annoying phenomena. The only question is how competent the analyst is to draw the right conclusions from the data that the machine issued. Among other things, to be sure of the necessity and importance of using Big Data, you can read the article on the Forbes website about nine benefits of embracing Big Data in human resources.
Conclusion On The Effectiveness of Big Data
Working with Big Data requires discretion and thoughtful use of information. Undoubtedly, automatic analysis of large data arrays facilitates the life of a business and helps to find new patterns and insights, which allows them to “squeeze out” the maximum benefit from their current state of affairs. This is a great tool for creating an effective business strategy. But, like any technology, Big Data has its dark side. Therefore, in order to achieve maximum efficiency, it is better to immediately take into account all the risks and minimize their occurrence in the future.
