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…
Category: cercana
Three Ways to Use GeoPandas in Your ArcGIS Workflow
Introduction When combining open-source GIS tools with the ArcGIS ecosystem, there are a handful of challenges one can encounter. The compatibility of data formats, issues with interoperability, tool chain fragmentation, and performance at scale come to mind quickly. However, the…
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
What is Strategic Planning and Why Does it Matter? Strategic planning is one of the most important things you can do for your organization. It helps you not only paint the picture of where you want your organization to be…
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,…
Hybrid Approaches to Geospatial Architectures
At Cercana, we have worked with geospatial systems that have run the gamut—from all-in proprietary stacks to pure open-source toolchains. As the technology landscape evolves, many organizations are blending both proprietary and open-source solutions. These hybrid architectures aim to capitalize…
Integrating AI Into Geospatial Operations
At Cercana, we’re excited by the constant evolution of geospatial technology. AI and its related technologies are becoming increasingly important components of geospatial workflows. Recently, our founder, Bill Dollins, has shared some of his explorations into AI through his personal…
Choosing Between an iPaaS and Building a Custom Data Pipeline
In today’s data-driven world, integrating various systems and managing data effectively is crucial for organizations to make informed decisions and remain responsive. Two popular approaches to data integration are using an Integration Platform as a Service (iPaaS) or building a…
Using Hstore to Analyze OSM in PostgreSQL
OpenStreetMap (OSM) is a primary authoritative source of geographic information, offering a variety of community-validated feature types. However, efficiently querying and analyzing OSM poses unique challenges. PostgreSQL, with its hstore data type, can be a powerful tool in the data…
Do You Need a Data Pipeline?
Do you need a data pipeline? That depends on a few things. Does your organization see data as an input into its key decisions? Is data a product? Do you deal with large volumes of data or data from disparate sources? Depending on the answers to these and other questions, you may be looking at the need for a data pipeline. But what is a data pipeline and what are the considerations for implementing one, especially if your organization deals heavily with geospatial data? This post will examine those issues.