services – Cercana Systems LLC

Geospatial Portfolio Management and Rationalization

2024-12-27 Cercana

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

2024-12-202024-12-20 Cercana

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

2024-08-282024-12-20 Cercana

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

2024-02-122024-02-12 Cercana

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

2023-12-052024-01-30 Cercana

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?

2023-05-172023-11-27 Cercana

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.