Introduction Geospatial data volumes and complexity are growing due to diverse sources, such as GPS, satellite imagery, and sensor data. Traditional geospatial processing methods face challenges, including scalability, handling various formats, and ensuring data consistency. The medallion architecture offers a…
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Three Ways to Use GeoPandas in Your ArcGIS Workflow
Applying Porter’s Five Forces to Open-Source Geospatial

Introduction The geospatial industry has seen significant transformation with the rise of open-source solutions. Tools like QGIS, PostGIS, OpenLayers, and GDAL have provided alternatives to proprietary GIS software, providing cost-effective, customizable, and community-driven mapping and spatial analysis capabilities. While open-source…
Developing a Geospatially-Aware Strategic Plan for Your Organization
The Importance of Metadata in Geospatial Data Portfolio Management

Managing geospatial data effectively is an important challenge for organizations that use location information for decision-making. Portfolio management for geospatial data involves organizing, evaluating, and prioritizing datasets to maximize their value while minimizing redundancy, inefficiency, and cost. However, such data…
Geospatial Portfolio Management and Rationalization

Many organizations rely on geospatial technology to derive insights based on location and spatial relationship. Whether they are mapping infrastructure, analyzing environmental changes, or optimizing logistics, managing geospatial investments effectively is imperative. Two strategies, IT portfolio management and IT rationalization,…