The Four V’s of Big Data

Big Data and analytics technologies enable your organisation to become more competitive and grow without limits. But if an organisation is capturing large amounts of data, it will need specific solutions for its analysis, such as an Intelligent Data Lake. But before we do that, let’s take a moment to analyse the value that Big Data brings to a company.

The 4 V’s of Big Data in infographics

IBM data scientists break big data into four dimensions: volume, variety, velocity and veracity. This infographic explains and gives examples of each.

Find the original infographic here.

The term “Big Data” is not new. For many people this term is directly associated with “a lot of data”. Understanding this technology in this way, however, is not entirely accurate. Big Data technology implies:

  • Compilation.
  • Storage.
  • Exploitation.

…of a large volume of data. However, this does not necessarily mean that we are talking about “Big Data”.

The 4 V’s of Big Data

It can be said that the Big Data environment has to have these four basic characteristics:


You may have heard on more than one occasion that Big Data is nothing more than business intelligence, but in a very large format. More data, however, does not necessarily mean it is Big Data.

Obviously, the Big Data, needs a certain amount of data, but having a huge amount of data, does not necessarily mean that you are working on Big Data.

It would also be a mistake to think that all areas of Big Data are business intelligence. The Big Data, is not limited or defined by the objectives sought with that initiative. But it will be by the characteristics of the data itself.


Today, we can base our decisions on the prescriptive data obtained through the Big Data. Thanks to this technology, every action of customers, competitors, suppliers, etc, will generate prescriptive information that will range from structured and easily managed data to unstructured information that is difficult to use for decision making.

Each piece of data, or core information, will require specific treatment. In addition, each type of data will require specific storage needs (the storage of an e-mail will be much less than that of a video).


This V will refer to both data quality and availability. When it comes to traditional business analytics, the source of the data is going to be much smaller in both quantity and variety. However, the organization will have more control over them, and their veracity will be greater.

When we talk about Big Data, variety is going to mean greater uncertainty about the quality of that data and its availability. It will also have its implications in terms of the data sources we may have.


It is very possible that Variety and Veracity would not be so relevant and would not be so much pressure when facing a Big Data initiative if it were not for the high Volume of information that has to be handled and, above all, for the velocity at which the information has to be generated and managed.

The data will be an input for the technology area (it will be essential to be able to store and digest large amounts of information). And the output part will be the decisions and reactions that will later involve the corresponding departments. The important thing here is that they are able to react with the necessary speed to boost the business area.

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