April 2025 Summaries

The text highlights several organizations using CARTO's spatial analytics capabilities to create positive environmental impacts. These include NetCarbon, which uses satellite data to fight climate change; Beyond Our Shores Foundation, which tracks Mahi-Mahi fish migration patterns to protect marine ecosystems; the Catalan Ornithological Institute, which empowers citizen scientists through collaborative mapping and data collection for bird conservation; and the National Renewable Energy Laboratory (NREL), which leverages spatial analytics to revolutionize renewable energy planning and emergency response systems. CARTO's platform enables these organizations to visualize complex environmental data in interactive and intuitive ways, facilitating decision-making and driving meaningful environmental action.

Google Cloud Next 2025 was a major event that brought together innovators, developers, and business leaders to explore the future of cloud technology. The event highlighted several exciting announcements, including the launch of new Workflows Extension Packages, which allow users to create custom low-code components for spatial analysis. These packages make it easier to automate repetitive tasks, ensure compliance with organizational processes, and share custom geospatial tools across teams. Additionally, Google announced an upcoming addition to one of these packages, the ST RegionStats component, which will enable users to calculate statistics in a polygon without writing any code. The event also showcased the potential of Agentic AI, democratization of analytics through low-code tools, and a commitment to data openness and accessibility. These developments are significant steps forward for organizations looking to unlock deeper insights from their data without complex infrastructure.

The KASPR Datahaus Cyber Intelligence data is now available on the CARTO platform, providing unparalleled insights into internet quality and performance. This proprietary technology consistently monitors over 400 million internet-connected endpoints globally, generating over 3 billion daily measurements to offer near-unprecedented insights into internet connectivity and quality at fine spatial granularity. The data encompasses 31,208 subnational regions spanning 216 countries and territories, shedding light on various metrics such as unique connected endpoint devices, average latency, fluctuations in latency, and specific latency measurements. This data can be used for applications like telecommunications monitoring, risk analysis, supply chain management, and machine learning analytics to enhance decision-making and mitigate risks related to internet infrastructure disruptions. The data is easily integratable into existing geospatial workflows and can be accessed through a cloud-native approach, making it a powerful tool for businesses and organizations relying on real-time data to navigate an increasingly connected world.

CARTO has introduced several new features in Q1 2025 to enhance its cloud-native spatial analytics platform. The company aims to push the boundaries of spatial analysis and visualization on top of leading cloud platforms, allowing users to break the GIS data silo and turn spatial data into real outcomes without compromising security and data governance. CARTO's latest updates include full capabilities to analyze and visualize raster data from a lakehouse, a QGIS plugin for editing cloud-hosted data, AI Agents for extracting geospatial insights from maps, enhanced secure connections with lakehouses, and more. These features aim to simplify workflows, improve performance, streamline spatial data analysis, and provide seamless integration with popular tools like QGIS and Databricks. Additionally, CARTO has introduced Workflows Extension Packages, allowing users to automate tasks and create reusable components, as well as support for Workload Identity Federation, Key-pair authentication, and OAuth authentication for secure connections between platforms. With these updates, CARTO is empowering users to unlock deeper insights with ease and take their spatial analysis to the next level.

The Snowflake ML extension for CARTO Workflows simplifies machine learning in spatial analytics by providing pre-built components to create, train, and deploy models. This allows GIS and data professionals to easily integrate forecasting and classification models into their workflows without requiring complex coding or deep technical expertise. The extension package includes functions such as classification and forecasting tools, enabling users to manage the complete ML pipeline within CARTO Workflows. A real-world example of crime forecasting in Chicago demonstrates how easy it is to use this extension to build a forecasting model, train it on historical data, evaluate its performance, and deploy it for future predictions. The tool empowers users to easily integrate predictive analytics into their spatial data workflows, making machine learning more accessible than ever.