But it also poses a new challenge: take advantage of the enormous volume of data, detect those that are useful from the great variety that exists, control them at the necessary speed, and have 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 our contemporary history. According to the consulting firm Gartner, in 2020, there will be more than 25 billion devices connected to the Internet, which suggests 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 by leaps and bounds every day. Due to the rapid evolution of technology and the habits and behaviors of society, companies are now in need of collecting, managing, and analyzing large amounts of data that, thanks to Big Data, can convert into information.

A precious source of knowledge about clients, competitors, the environment, etc., with which you 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, 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 feature of Big Data refers to the size of the amounts of data that are currently generated.

The figures are staggering. And it is that the data that is produced in the world for two days is equivalent to all that generated before 2003. These large volumes of data that are produced at any time pose significant technical and analytical challenges for the companies that manage them. 

# 2 Speed

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 This large volume causes data to become out of date quickly and to lose its value when new data appear.

Businesses, therefore, must react very quickly 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 other fields must also work at high speed to convert that data into useful information before it loses its value.

# 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 come 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, later, combining and configuring some data with others. 

Each type of information is treated differently, through 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 the data storage and analysis processes increases.

# 4  Truthfulness

This feature of Big Data is probably the most challenging. The large volume of data generated can make us doubt the degree of integrity 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, whether the data comes from different countries or if providers use varying formats. These data must be cleaned and analyzed, a continuous activity since new ones are continuously generated. Uncertainty regarding the veracity of the data may cause certain doubts about its quality and availability in the future. 

For this reason, companies must ensure that the data they are collecting is valid, that is, that it is adequate for the objectives that they intend to achieve 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 an essential 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, create personalized offers to customers, increase relations with the public, and much more.

To be aware of all the opportunities that can be extractedicle through the application of Big Data, it is necessary to understand what are the main elements that add value to it and make its implementation 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 give us your opinion.

Related Article: Small Data: Big Data For SMEs

The post What Are The 5 V’s Of Big Data? appeared first on Stuff In Post.