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Big Data

It involves the use of large amounts of data that are collected and processed to obtain valuable information and discover patterns and trends. Big Data can come from a variety of sources, such as enterprise databases, medical data, mobile devices and sensors. Big Data processing requires specialized technologies and tools, such as machine learning algorithms and HPC (high performance computing) systems, to analyze and derive valuable information from the data. Big Data can be used to improve decision making in companies, optimize production processes and improve the efficiency of public services.


Data storage and processing environments used to manage and analyze large amounts of information.

These spaces are characterized by their ability to store and process large amounts of data quickly and efficiently, and by their capacity to integrate different data sources.

These data spaces allow data to be shared among different agents, a practice that can be beneficial for companies as it allows them to access new knowledge and opportunities.

For a correct use of data spaces, data sovereignty and governance must be well defined.

Data sovereignty refers to the right of an individual or an organization to have control over their personal data and to decide how it is used and shared.

On the other hand, data governance refers to the way decisions are made about the use and sharing of data in an organization or community. This includes defining policies and processes for data collection, storage and use, as well as creating mechanisms to ensure compliance with these policies.


The process of gaining access to data that is stored in a data space or data repository.

Data sets can be of different types, such as structured, semi-structured or unstructured data, and can be used for different purposes, such as research, data analysis or decision making.


Data collection is the process of obtaining information from different sources and storing it for later analysis.

Sensorization is a technique used to collect data through devices called sensors.

Thanks to data collection and sensorization, it is possible to obtain accurate, real-time information that can be used to make informed decisions and improve processes.


Processes used to extract valuable information from data sets.

Data analysis involves examining data systematically to discover patterns and relationships, while data mining involves using this information to make decisions and improve processes.


It consists of graphically representing data or information in a way that is easy to understand and analyze.

Information visualization is used to present data in a clear and concise manner, and allows users to better understand the information and draw conclusions from it.


Concepts that refer to the process of ensuring that an organization’s or individual’s data is protected and used appropriately.

Data protection refers to measures taken to protect information from unauthorized access or cyber attacks.

Data governance, on the other hand, refers to the way in which an organization’s data is used and managed.

This includes aspects such as defining data usage policies, managing data access rights and implementing compliance measures with specific regulations.