Big Data

May 13, 2024

The 5 V of Big Data

Currently, we know that the secret to a successful digital transformation and being a company that bets on using data to improve its operations (data driven company) lies in handling data correctly.

Every day, at every moment, new data is created massively. This is what we know as Big Data, a large volume of data that is generated and must be stored, processed, and interpreted optimally to turn that information into knowledge. Carrying out these tasks is possible thanks to new technologies.

At the business level, the correct use of data can help improve customer service, make better decisions, predict risks early, or improve efficiency, among many other uses.

But to make a good interpretation of them and benefit from all their advantages, you must know their characteristics, also known as the 5 V's of Big Data, which describe the challenges and opportunities of working with large data sets. Here we go!

big data
  1. Volume
    We live in a digitalized world where any movement can be tracked and generated in the form of data due to the increase in connected devices, social networks, e-commerce, sensors, automated records, etc. As of today, each person produces approximately 2 MB of data every second and it is predicted that this amount will double every year. Every minute, around 188 million emails are sent and about 4.5 million searches are made on Google.Big data technology requires collecting a very high dose of information that accumulates day by day, which poses a challenge, both in terms of storage and processing.
  2. Speed
    The V of speed is the rapidity at which data is created, processed, and stored in order to be interpreted in real time and to be able to take action as soon as possible. This data is collected and analyzed instantly, without waiting for all the data to be collected to start the analysis.
    To make this possible, there must be an infrastructure and appropriate technologies, as well as algorithms and analysis techniques to handle real-time data.
  3. Variedad de tipos
    The data collected comes from different sources such as websites, sensors, mobile devices, social networks, among others, and in different formats such as video, text, numbers, images, audio, or metadata.
    Hay que tener en cuenta que la información debe tratarse de manera diferente según el tipo que sea. Por esta razón, se necesitan diferentes herramientas y técnicas ya que, por ejemplo, no es lo mismo procesar un texto que una imagen.
  4. Veracity
    The information obtained is highly reliable, but it is important to consider that the greater the variety of data and the speed at which it is generated, the less accurate the data is. Therefore, it will be necessary to validate and clean it before processing it in order to draw valuable conclusions that can be used, among other things, to gain in-depth knowledge of customers, predict possible events, detect problems, etc.Just as important as obtaining the data is how to process it correctly, and for this, the way of visualizing it plays a very important role. It is necessary to look for tools that adapt to the volume of data and group them, whenever possible, to facilitate their analysis graphically or in dashboard mode.
  5. Value
    The value of the data comes from the information extracted from it, which can be transformed into knowledge that helps make decisions more quickly and effectively. However, it is important to consider that data by itself has no value and it will always be necessary to process and analyze it to extract the information needed in each case.
    A direct value is the way to monetize that data, for example, helping the CMO better understand customers and find techniques to retain them.


Analyzing data can have a very positive impact on organizations, both to improve their services or products, reduce costs, increase efficiency... because by identifying behavior patterns, trends, or other useful data, more precise decisions can be made.

If you are thinking about improving decision-making by implementing big data, contact us!

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