11 posts found
How local councils drive open data in municipalities
Although local governments are the closest actors to citizens, they often face limitations in terms of resources and capacities to implement open data effectively. The diputations, as intermediate institutions between central government and municipalities, play a key role in coordinating, supporting…
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…
How to measure carbon footprint using open data
The carbon footprint is a key indicator for understanding the environmental impact of our actions. It measures the amount of greenhouse gas emissions released into the atmosphere as a result of human activities, most notably the burning of fossil fuels such as oil, natural gas and coal. These gases,…
Accelerating the energy transition with open data
Aspects as relevant to our society as environmental sustainability, climate change mitigation or energy security have led to the energy transition taking on a very important role in the daily lives of nations, private and public organisations, and even in our daily lives as citizens of the world. Th…
MAMD Methodology: The Alarcos Model of Data Improvement
There is such a close relationship between data management, data quality management and data governance that the terms are often used interchangeably or confused. However, there are important nuances.
The overall objective of data management is to ensure that data meets the business requirements tha…
The benefits of open data in the agriculture and forestry sector: the case of Fruktia and Arbaria
As in other industries, digital transformation is helping to change the way the agriculture and forestry sector operates. Combining technologies such as geolocation or artificial intelligence and using open datasets to develop new precision tools is transforming agriculture into an increasingly tech…
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…
