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Digitisation and Big Data, how to do both at the same time?

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Digitisation and Big Data, how to do both at the same time?

Before the arrival of the Internet, computers were a technological revolution and before that, telephones. Thanks to all the technological devices our society has advanced by leaps and bounds in recent years.

All this has also meant that all the aspects surrounding digitalization, now also serve to cover different needs applicable to both personal and professional.

Managing digitalization and big data together


When digitalization and big data applied to processes are managed together, great results are achieved, such as

  • Predicting behavior.
  • Predicting searches within a system.

However, you should know that the only way to do this first is to take a first step that would be the digitization of the process to later have a database that can be fed, analyzed and adding valuable content to the processes.

The truth is that digitizing the entire company and its activities will be a long process. However, it will be the tip of the iceberg in terms of the information that can be collected in the company. Once the data is organized, it will become crucial information for decision making, which can be used to cover and optimize the company’s resources.

The term “Big Data” owes its name to the computer scientist John Masheley. This person focused his career on massive data, and argued that there would be a time when data would be generated in a massive way, challenging the world of computing and causing old IT infrastructures to be changed, driving two things:

  • Virtuality.
  • Digitalization.

Precise data, the most efficient


The more precise a data is, the more value it has, being more efficient. To be able to work in a process of digitizing large volumes of information, you will have to follow some requirements in terms of storage. The most recommendable is that you use repetitive patterns as this will facilitate the search and manipulation of the data.

Having a process and a technological structure will be indispensable for any professional who processes data, managing to optimize their work.

For the Big Data to work efficiently, when we carry out the digitalization of the information, you will also have to comply with certain parameters of “clean” and data organization. Otherwise, you will not get the results you are looking for, and the statistics will not reflect the real da

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