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GET IN TOUCHPublished 26/09/2023
Hello Freddie. Could you introduce yourself and what you do at Aya Data and what you specialize in? I founded Aya with our COO, Ama, in order to create an ethical data collection and annotation service – which we saw a huge need for. We quickly developed a specialism in Geospatial annotation – and […]
Published 21/09/2023
In today’s data-driven world, geospatial data science has emerged as a pivotal field with applications spanning industries like agriculture, urban planning, environmental science, and beyond. The market is projected to reach USD 845.7 billion in value by 2029 at a CAGR of 16.9%, so it’s clearly rapidly expanding. Yet, the concept of ‘geospatial data science’ […]
Published 15/09/2023
In today’s data-driven world, businesses and organizations are constantly seeking innovative ways to harness the power of data to make informed decisions. One such method that has gained prominence in recent years is geospatial predictive analysis. By combining the capabilities of predictive analytics with geographic information systems, geospatial predictive analysis offers a unique and powerful […]
Published 08/09/2023
In an era where data drives decision-making across industries, geospatial data analysis has emerged as a critical tool for understanding our world in a whole new dimension. From urban planning to disaster management, geospatial data allows for deeper insights into phenomena and events than ever before. In this article, we will take a closer look […]
Published 04/09/2023
While many consider the technology to still be in its infancy, geospatial AI solutions have already demonstrated the ability to automate many manual processes and provide analyses far more quickly and more accurately than humans can, while using fewer resources – given the right conditions. In this article, we will discuss geospatial AI use cases […]
Published 31/08/2023
The basis of all machine learning projects is data collection and acquisition. But that is also the first stumbling block where many ML projects fail. In this article, we will discuss the challenges of text, audio, photo, and video data collection for ML training models so that you can predict and avoid the many pitfalls. […]