What are the 5 V’s of Big Data?

What are the 5 V’s of Big Data?

When we realize that all our information is online, we may feel skepticism and, perhaps, insecurity. But this fact can hardly be avoided today. We live in a hyper-connected era in which the evolution of technologies increases globalization and in which data is generated every second. Big Data is configured as a great opportunity for the market and of companies to improve their strategies and decision-making.

 

But it also poses a new challenge: taking advantage of the enormous volume of data, detecting those that are useful from the great variety that exists, controlling them at the necessary speed, and having knowledge about their veracity. Surely you know what Big Data is, but do you know the 5 V’s of Big Data? We explain them to you!

Big Data, from data to valuable information

Big Data is one of the fundamental keys to improving corporate governance. And it is that more data is generated in two days than in all of our contemporary history. According to the Gartner consultancy, in 2022 there will be more than 25 billion devices connected to the Internet, which gives us a glimpse that the volume of data contained in Big Data will grow exponentially.

 

The digital transformation of structures, processes, and tools allows the Big Data environment to grow every day by leaps and bounds. Due to the rapid evolution of technology and the habits and behaviors of society, companies are now faced with the need to collect, manage and analyze large amounts of data that, thanks to big data, they can convert into information.

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A very valuable source of knowledge about customers, the competition, the environment, etc., with which to define better strategies to achieve your objectives and obtain competitive advantages.

 

The 5 V’s of Big Data 

Big Data is made up of five dimensions that characterize it, known as the 5 V’s of Big Data. Let’s see what each of these aspects consists of:

 

# 1  Volume

Traditionally, the data has been generated manually. Now they come from machines or devices and are generated automatically, so the volume to be analyzed is massive. This characteristic of Big Data refers to the size of the amounts of data that are currently generated.

 

The numbers are staggering. And the fact is that the data that is produced in the world during two days is equivalent to all that generated before the year 2003. These large volumes of data that are produced at all times pose important technical and analytical challenges for the companies that manage them.

 

# 2  Speed

The flow of data is massive and constant. In the Big Data environment, data is generated and stored at unprecedented speed. This large volume causes data to quickly become out of date and lose its value when new ones appear.

Companies, therefore, must react very quickly to be able to collect, store and process them. The challenge for the technology area is to store and manage large amounts of data that are continuously generated. The rest of the areas must also work at high speed to convert that data into useful information before it loses its value.

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# 3  Variety

The origin of the data is highly heterogeneous. They come from multiple supports, tools, and platforms: cameras, smartphones, cars, GPS systems, social networks, travel records, bank movements, etc. Unlike a few years ago, when the data that was stored was extracted, mainly, from spreadsheets and databases.

The data that is collected can be structured (they are easier to manage) or unstructured (in the form of documents, videos, emails, social networks, etc.).Depending on this differentiation, each type of information will be treated differently, through specific tools. The essence of Big Data resides in, subsequently, combining and configuring some data with others.

 

Each type of information is treated differently, using specific tools, but then the essence of Big Data lies in combining and configuring some data with others. It is for this reason that the degree of complexity in data storage and analysis processes increases.

 

# 4  Truthfulness

This feature of Big Data is probably the one that poses the greatest challenge. The large volume of data that is generated can make us doubt the degree of veracity of all of them since the great variety of data causes many of them to arrive incomplete or incorrect.

This is due to multiple factors, for example, if the data comes from different countries or if the providers use different formats. This data must be cleaned and analyzed, an incessant activity since new ones are continually generated. The uncertainty as to the veracity of the data can cause certain doubts about its quality and its availability in the future.

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For this reason,  companies must ensure that the data they are collecting is valid, that is, that it is adequate for the objectives that are intended to be achieved with it.

 

# 5  Value

This characteristic represents the most relevant aspect of Big Data. The value generated by the data once converted into information can be considered the most important aspect. With this value, companies have the opportunity to make the most of the data to introduce improvements in their management, define more optimal strategies, obtain a clear competitive advantage, make personalized offers to customers, increase the relationship with the public, and much more.

 

To be aware of all the opportunities that can be extracted through the application of Big Data, it is necessary to understand what are the main elements that add value and that make its application at the business level a safe bet. And you, where do you think the success of Big Data lies? Do not hesitate to comment and leave us your opinion. Also in this video, we explain what the Big Data expert is so that you have no doubts about this profession of the future.

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