11 posts found
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…
GeoPackage in INSPIRE: efficiency and usability for geospatial data geospatial data.
In the field of geospatial data, encoding and standardisation play a key role in ensuring interoperability between systems and improving accessibility to information.
The INSPIRE Directive (Infrastructure for Spatial Information in Europe) determines the general rules for the establishment of an Inf…
A common language to enable interoperability between open dataset catalogs
Open data plays a relevant role in technological development for many reasons. For example, it is a fundamental component in informed decision making, in process evaluation or even in driving technological innovation. Provided they are of the highest quality, up-to-date and ethically sound, data can…
Legal implications of open data and re-use of public sector information for ChatGPT
The emergence of artificial intelligence (AI), and ChatGPT in particular, has become one of the main topics of debate in recent months. This tool has even eclipsed other emerging technologies that had gained prominence in a wide range of fields (legal, economic, social and cultural). This is t…
When to use each programming language in data science?
Python, R, SQL, JavaScript, C++, HTML... Nowadays we can find a multitude of programming languages that allow us to develop software programmes, applications, web pages, etc. Each one has unique characteristics that differentiate it from the rest and make it more appropriate for certain tasks. But h…
10 Popular natural language processing libraries
The advance of supercomputing and data analytics in fields as diverse as social networks or customer service is encouraging a part of artificial intelligence (AI) to focus on developing algorithms capable of processing and generating natural language.
To be able to carry out this task in the current…
10 Popular Data Analytics and Machine Learning Libraries
Programming libraries refer to the sets of code files that have been created to develop software in a simple way . Thanks to them, developers can avoid code duplication and minimize errors with greater agility and lower cost. There are many bookstores, focused on different activities. A few weeks ag…
11 libraries for creating data visualisations
Programming libraries are sets of code files that are used to develop software. Their purpose is to facilitate programming by providing common functionalities that have already been solved by other programmers.
Libraries are an essential component for developers to be able to program in a simple way…
Why should you use Parquet files if you process a lot of data?
It's been a long time since we first heard about the Apache Hadoop ecosystem for distributed data processing. Things have changed a lot since then, and we now use higher-level tools to build solutions based on big data payloads. However, it is important to highlight some best practices related to ou…
R and Python Communities for Developer
R vs Python? Better R and Python: Two languages, two styles. A common goal: to domesticate the data.
If data science were a sport, R and Python would be the two best teams in the league for several seasons. If you are a Data Scientist or are close to this scientific-technical discipline, the two pro…
