What is Big Data? The term appeared in 2008. For the first time it was used by the editor of the journal Nature – Clifford Lynch. He talked about the explosive growth of world information and noted that they should master new tools and more advanced technologies.
To understand it, you need to define the concept and its function in marketing. These days, they generate data on a regular basis: when they open an application, search on Google, shop online, or just travel with a smartphone in their pocket. The result is huge amounts of valuable information that companies collect, analyze and visualize.
This term defines bodies of information that cannot be analyzed or analyzed using methods using human labor and desktop computers. The peculiarity is that the data array continues to grow exponentially over time, therefore, the processing power of supercomputers is required for the operational analysis of the collected materials. Consequently, processing requires cost-effective, innovative methods of processing information and delivering inferences.
But why put so much effort into organizing and analyzing Big Data? Big data analytics are used to understand the attractiveness of goods and services, predict market demand and reaction to an advertising campaign. Working with hire big data developers firms attract more customers and increase revenues, use resources efficiently and build a competent business strategy.
This means that analysts who can extract useful information are in great demand right now. You can learn this even if you have never worked in IT. For example, GeekBrains’ Faculty of Analytics offers convenient online classes and a dozen case studies in its portfolio. By the way, the first six months of training are free. Those who have successfully completed the course will definitely be employed – this is spelled out in the contract:
- tasks in the field of analytics and management: to raise the awareness of managers and the competence of employees in the field of Data science and Big Data;
- go from the tasks set, and not from the need to collect it and use new technologies;
- remember that they are not analytic hackers, but work in a team of like-minded people (analysts + business + IT);
- create analytical laboratories based on the ecosystem as the first step in mastering advanced analytics.
Imaginary and Real Dangers of Big Data
Recently, a lot of research has been carried out in the field of so-called big social data. A number of experts regard this area as a separate science. Four significant sub-areas can be distinguished here – social computing, big data science, analytics, and computational social science (CSS). Scientist Hiroshi Ishikawa is an adept in approaching sociological it as a science. He defines social data as social media, which is a type of big data with the characteristics of four Vs – volume, variety, velocity, vague. Diversity in this context implies fragmentation, structuredness or their partial structuredness. Speed characterizes the development of data in dynamics, is constantly growing, which is why they need to be processed quickly to obtain results.