Brett Parker The Five "Vs" of Big Data

Brett Parker Sap - Big data (big data or large volumes of data) is an evolutionary term that describes any voluminous amount of structured, semi-structured and unstructured data that has the potential to be mined for information.

 

Big Data can be classified through its four main characteristics, also known as the four Vs of Big Data (volume, variety, speed and truthfulness). To these, three more can be added: feasibility, visualization and value.

The first question that comes to mind when considering what Big Data is and what it is for is related to how much "big" the data has to be to be considered "Big".

 

 

Brett Parker Sap - Finally, the correct approach is not to set a size at all, but relative. What may now seem like a large size of data, in two or three years may be normal or even irrelevant. Most experts define Big Data in terms of the five "Vs":

Brett Parker Sap Volume: As we have seen, the amount of data is defined “Big” not when it exceeds a defined size, but when its storage, processing and exploitation begins to be a challenge for an organization.

 

Speed: The second characteristic of Big Data is related to the rate at which data is being generated, which is constantly increasing and which needs a real-time response from companies.

Variety: however, the main challenge of Big Data lies in the great difference in different formats in which we find the data and which can range from simple text, to images, videos, spreadsheets and entire databases.

 

Accuracy: In addition, the data has to be reliable and has to be kept clean. A large amount of data is worthless if it is incorrect and can be highly damaging, especially in automated decision making.

 

Value: finally, the data and its analysis must generate a benefit for companies.

 

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