Big data

Big Data

Although we may not realize it, we are surrounded by data from different sources on a daily basis. And in an era dominated by technology, every action performed leaves a data record without us noticing it. As time goes by, this information grows exponentially until it reaches enormous amounts of storage size. You may think of this data as simple space-spanning records, however it is more valuable than we think. Companies are increasingly seeking to position themselves better and to do so they must offer better products or services. It is here where big data proves its utility, as it serves as a basis for making improvements or even solving problems.

What is Big Data?

It is a massive set of data that grows over time, filling company databases in the blink of an eye. The size and growth rate of these data packages is such that you cannot process them with conventional equipment. Despite the difficulty of processing and managing this data, it is one of the best sources of information for companies. However, it is not about how much data you get, but how you analyze it and implement it in the improvement of any field.

However, we can also refer to the term Big Data as the process of analyzing large volumes of data. All this, in order to find information to apply in different areas of the companies.


To understand the concept of Big Data, it is necessary to know its features, which we call "the three Vs". These are:


Consists of the level of data production over a period of time, which can come from different sources. Depending on the company type, the amount of information varies greatly. Volume is one of the most important features because it can generate a better analysis with more resources. However, the utilization process gets harder as the amount of data increases.


It is the speed at which we receive and analyze information packages in companies. Receiving and analyzing information can be even faster by transferring everything into a memory instead of saving it on a disk. In this way, this process is performed practically in real time. However, in order to work in this way, it is necessary to evaluate and act in real time in the same way.


It refers to the types of data that the company has in its possession, which may be similar or completely varied. They can be structured, unstructured and semi-structured.

  • Structured data: They contain a familiar fixed format and are easy to store, usually as a numerical file.
  • Unstructured data: They are a challenge due to their unfamiliar structure. They are difficult to process due to their size.
  • Semi-structured data: Their format may vary between the two previously explained. Although you may be able to recognize its format, you may not be able to understand it, requiring other resources for processing.

Big Data examples

One of the best ways to understand the utility of Big Data analysis is through examples. Here are some incredible examples:

Marketing and sales

To sell a product you only need to know the preferences of a given population. Through massive amounts of information, you can learn more about the tendencies of potential buyers. Not only will it be useful to determine which products are popular, but also to develop marketing campaigns.


In the investment world, a single decision can make a big change for a company. This is why any type of information is necessary in order to avoid risks. By studying the information, you can evaluate an event or situation better and make the right decision.


The media regularly use this type of analysis to design strategies to improve their viewer ratings. One of the most used channels to obtain information is the social media, a space where it is possible to know what people think. Whether through comments, hashtags or polls, the information that you find will be plentiful. 

Big Data uses

 Massive information packages are very useful for companies, since they can apply them in different areas. These are some of its most common uses:

Product development

Through receptivity studies of various company products, a company can learn how they are viewed by consumers. By studying the receptivity of a company's products, it can find out which aspects to improve in order to create new products. By knowing consumers' tastes and opinions, companies develop products that they then recommend to their customers.

Customer experience

Customer experience is one of the most important aspects when offering a product or service. One way to collect useful data is through social networks and websites, providing valuable information for improvements. By analyzing users, you can improve their experience when testing a product or service, achieving their complete satisfaction.

Failure prediction

In addition to improving products and user experience, a company needs to avoid major risks. Depending on the type of data received, the company can detect a potential threat. Therefore, effective action can be taken before the problem arises.

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