Big Data – a whole science

Nowadays the technologies of Big Data class attract a big attention of people. Of course, it is associated with a permanent increase of data. Every day the
processing of stored information becomes more difficult and more expensive
, despite the fact that it is value of many organizations.
But how safe is this storage and is there a limit on the quantity of data?
The actively developing tools are used nothing but for a terabyte of data and it is difficult to imagine which financial investment are required for the development of Big Data technology. The information should not to be only accumulated but also be useful , that is why Big Data is considered as a whole science. Until now there is a problem of lack of professionals in this branch and there is no understanding which data should be ignored and which be collected and stored.
With the help of Big Data marketers can predict the future of the company. Because every time when we surf the Internet the search engines etc. collect personal information about the user in order to show us the specific advertisement. With this point of view businessmen can get to know better their customers and introduce new methods which increase customer’s confidence.
Huge amount of data is operated without our knowledge disturbing our the privacy and confidentiality. The storage of such data increases the risk of information security and it becomes virtually impossible to keep anonymity.
The question of security is on the first place and depends simpliciter on other factors: a limited budget, the complexity of integration with existing systems, the number of data providers.
Modern viral hackers attacks are so active that even super-protected servers
of government security forces can`t hold them back.
But in the same time Big Data technology helps catch criminals. With the help of analysis of a big amount of data you can determine the most criminal city`s regions or withstand financial fraud.
In this way when we talk about a big data we should understand so far as a big volume of data exists it must be able to filter the data out and finished very quickly. On the other hand, this term is often understood as a set of tools and technologies that will be able to solve specific problems.
Distributed computing system underlies all of this where processing of large volume of data needs for itself not one high-performance machine but a whole group of such machines, which are clustered.