12 posts found
AI Data Readiness: Preparing Data for Artificial Intelligence
Over the last few years we have seen spectacular advances in the use of artificial intelligence (AI) and, behind all these achievements, we will always find the same common ingredient: data. An illustrative example known to everyone is that of the language models used by OpenAI for its famous ChatGP…
PET technologies: how to use protected data in a privacy-sensitive way
As organisations seek to harness the potential of data to make decisions, innovate and improve their services, a fundamental challenge arises: how can data collection and use be balanced with respect for privacy? PET technologies attempt to address this challenge. In this post, we will explore what…
High value statistical datasets foreseen in the National Statistical Plan 2021-2024
The year 2023 was undoubtedly the year of artificial intelligence. This has brought data, and therefore open data, back to the forefront, as it is the raw material that fuels this technology, which is key to value creation in our increasingly digital economy.
Perhaps that is why 2023 has also l…
New Year's resolution: Apply the UNE data specifications in your organisation
As tradition dictates, the end of the year is a good time to reflect on our goals and objectives for the new phase that begins after the chimes. In data, the start of a new year also provides opportunities to chart an interoperable and digital future that will enable the development of a robust data…
Application of the UNE 0081:2023 Specification for data quality evaluation
The new UNE 0081 Data Quality Assessment specification, focused on data as a product (datasets or databases), complements the UNE 0079 Data Quality Management specification, which we analyse in this article, and focuses on data quality management processes. Both standards 0079 and 008…
UNE 0081 Specification - Data Quality Assessment Guide
Today, data quality plays a key role in today's world, where information is a valuable asset. Ensuring that data is accurate, complete and reliable has become essential to the success of organisations, and guarantees the success of informed decision making.
Data quality has a direct impact not only…
FAIR principles: the secret of the data wizards.
Books are an inexhaustible source of knowledge and experiences lived by others before us, which we can reuse to move forward in our lives. Libraries, therefore, are places where readers looking for books, borrow them, and once they have used them and extracted from them what they need, return them.…
Data visualization: the best charts for representing comparisons
Data is a valuable source of knowledge for society. Public commitment to achieving data openness, public-private collaboration on data, and the development of applications with open data are actions that are part of the data economy, which seeks the innovative, ethical, and practical use of data to…
Free tools to work on data quality issues
Ensuring data quality is an essential task for any open data initiative. Before publication, datasets need to be validated to check that they are free of errors, duplication, etc. In this way, their potential for re-use will grow.
Data quality is conditioned by many aspects. In this sense, the Aport…
Technical Standards to achieve Data Quality
Transforming data into knowledge has become one of the main objectives facing both public and private organizations today. But, in order to achieve this, it is necessary to start from the premise that the data processed is governed and of quality.
In this sense, the Spanish Association for Standardi…
