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What is Big Data?

(3 minute read)

Origin

Erik Larson mentioned the term Big Data for the first time in 1989, but it was in the late 1990s that business intelligence tools to monitor and analyze business performance became popular.

The generation, consumption and analysis of big data begins with the creation of the www. (world wide web), which made it possible to begin to manage and analyze an endless amount of data not available to the public until then, creating new opportunities for companies.

In order to be aware of the current dimension of the data, we highlight the note of Eric Schmidt, executive president of Google, who stated that currently as much data is created every two days, as there is from the beginning of civilization until the year 2003.

 

Definition

As Reyes Mas indicates, Head of Artificial Intelligence at Bionline, indicates, the term Big Data refers to the treatment of data sets that are generated at high speed and are of such volume, complexity and availability that special techniques and infrastructure are required to be able to carry it out successfully. In this way, the traditional approach must be replaced by new data storage and processing techniques.

 

Characteristics: the 5 V’s

Regarding Big Data, the 5 V’s that characterize it are taken into consideration, which we will develop below.

1. Volume: Big Data always involves massive amounts of data (terabytes).

2. Variety: the data comes from different sources and can have different formats. In other words, not only do you work with structured data from databases, but also with unstructured data, such as images, videos, audios, tweets …

3. Veracity: it is necessary to be able to ensure that the data used is truthful and of quality, since decision-making based on data that is not data can have serious consequences for the business.

4. Speed (velocidad, in Spanish): data is generated at high speed, which requires the development of systems that are capable of processing it properly. In this sense, speed and handling of data in real time are essential.

5. Value: it is also crucial to ensure that the data add value to the business. To avoid a great opportunity cost, we must be able to convert this data into useful information.

 

Conclusion

The greatest complexity in dealing with Big Data lies in determining what data should be used and how it should be processed efficiently to obtain value from it. Undoubtedly, the correct exploitation of this type of data increasingly reinforces the competitive advantage of companies that rely on our technology.

 

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