31 posts found
How to prepare your data to work with artificial intelligence tools from a legal point of view
The idea of conceiving artificial intelligence (AI) as a service for immediate consumption or utility, under the premise that it is enough to "buy an application and start using it", is gaining more and more ground. However, getting on board with AI isn't like buying conventional software and gettin…
Altruistic projects to create AI models in co-official languages
Artificial intelligence (AI) assistants are already part of our daily lives: we ask them the time, how to get to a certain place or we ask them to play our favorite song. And although AI, in the future, may offer us infinite functionalities, we must not forget that linguistic diversity is still a pe…
Data governance in smart grids: from the meter to the energy strategy
Energy is the engine of our society, a vital resource that powers our lives and the global economy. However, the traditional energy model faces monumental challenges: growing demand, climate urgency, and the prevailing need for a transition to cleaner and more sustainable sources. In this panorama o…
Federated machine learning: generating value from shared data while maintaining privacy
Data is a fundamental resource for improving our quality of life because it enables better decision-making processes to create personalised products and services, both in the public and private sectors. In contexts such as health, mobility, energy or education, the use of data facilitates more effic…
Industrial data governance: the basis for more efficient and sustainable production
Today's industry is facing one of the biggest challenges in its recent history. Market demands, pressure to meet climate targets, consumer demand for transparency and technological acceleration are converging in a profound transformation of the production model. This transformation is not only aimed…
ALIA and foundational models What are they and why are they key to the future of AI?
The enormous acceleration of innovation in artificial intelligence (AI) in recent years has largely revolved around the development of so-called "foundational models". Also known as Large [X] Models (Large [X] Models or LxM), Foundation Models, as defined by the Center for Research on Foundation Mod…
Data Mesh and Data Fabric: New Perspectives in Enterprise Data Architectures
Over the last decade, the amount of data that organisations generate and need to manage has grown exponentially. With the rise of the cloud, Internet of Things (IoT), edge computing and artificial intelligence (AI), enterprises face the challenge of integrating and governing data from multiple sourc…
Common mistakes in the development of a data strategy
In an increasingly data-driven world, all organisations, both private companies and public bodies, are looking to leverage their information to make better decisions, improve the efficiency of their processes and meet their strategic objectives. However, creating an effective data strategy is a chal…
Using Pandas for quality error reduction in data repositories
There is no doubt that data has become the strategic asset for organisations. Today, it is essential to ensure that decisions are based on quality data, regardless of the alignment they follow: data analytics, artificial intelligence or reporting. However, ensuring data repositories with high levels…
Data job offers: The most valued skills on the market
Almost half of European adults lack basic digital skills. According to the latest State of the Digital Decade report, in 2023, only 55.6% of citizens reported having such skills. This percentage rises to 66.2% in the case of Spain, ahead of the European average.
Having basic digital skills is essent…
