In 2021, the Geospatial Analytics market was estimated to be $59.5 billion. By 2026, that number is expected to explode to $107.8 billion. Geospatial Analysis has widespread applications across the globe, from being used to further business interests to aiding humanitarian initiatives. In the middle of a global pandemic, geospatial…

What if there was a way for computers to analyze and convert raw data into simple, human language? Fortunately, this is already being done today via Natural Language Generation (NLG). While we human beings continue to adapt and evolve our skills in various scientific fields, it’s our ability to understand…

Man-made climate change has increased the frequency and the severity of calamities such as droughts, floods, famines, and hurricanes. This has led to automating disaster preparedness and recovery actions using AI and ML solutions. In the past 50 years, the number of recorded disasters has increased five times, and the…

In 2017, when Hurricane Harvey was on a devastative spree in Texas, disaster recovery organizations trusted census data to deploy emergency evacuation and management programs. The census data revealed that 86% of the population living in the zip code 77011 spoke Spanish. …

Spatial analysis is one of the vital aspects of GIS (Geographic Information System). It allows you to use independent sources and conclude results through a set of spatial tools. As data-driven decision-making is on the rise, the application of spatial across businesses and non-profits has increased manifold in recent years. …

The advent of data has been tremendous in recent years, all thanks to the rising influence of technology in our daily lives. Data can be in multiple forms. Text data is one of them and is available in the forms of survey responses, emails, social media posts, customer queries or…

The information age has brought with it a deluge of data, both structured and unstructured. The collection of data is growing every single day. In this, it is estimated that a staggering 80 to 90% is unstructured. The growth rate of unstructured data is about 65%. …

Machine learning has evolved its use cases in Species detection. This has resulted in making conservation researchers, and non-profit organizations self-sufficient to use data and technology to save species. …

Digital Twins are a new class of enterprise software that uses streaming data from IoT devices to monitor, analyze, and predict the operation of equipment and processes. …