A Geospatial Data Analyst explores and interprets spatial data to uncover patterns and insights. They support decision-making in areas such as urban planning, environment, mobility, and public policy. Typical tools include GIS software, data analysis platforms, and visualization tools.
A Geospatial Data Analyst works mainly with existing datasets to extract meaning from geographic information. During a typical week, they clean and combine spatial and non-spatial data, perform analyses, and translate results into clear maps, charts, or dashboards. In addition, they collaborate with domain experts to understand questions and choose the right analytical approach. Although most work happens behind a computer, analysts regularly discuss findings with stakeholders and explain spatial trends in an accessible way.
…and many other fields where data-driven spatial insight matters.
This role suits people who enjoy discovering patterns in data and turning complexity into clarity. If you like asking analytical questions, working with real-world datasets, and explaining insights visually, this career can be highly motivating. Moreover, the work often contributes directly to better planning, sustainability, and smarter decision-making, which gives many analysts a strong sense of purpose.
Do you have questions about the course content? Not sure if the course aligns with your learning objectives? Or would you prefer a private session or in-company training? We’re happy to assist—feel free to get in touch.
Geography, GIS, Geomatics, Data Science, or a related field
Or equivalent experience through projects or training
QGIS — Blended Learnings: QGIS Basics, QGIS Advanced
Python for data analysis — Blended Learnings: Python Basics, Python Advanced, Python for Geospatial Development
SQL & spatial databases — Blended Learnings: SQL Basics, PostgreSQL
Power BI for spatial data — Course in Dutch
Statistics for geodata — Course in Dutch
Demand for geospatial analysts continues to grow as organizations increasingly rely on data-driven insights. As a result, opportunities expand in smart cities, climate adaptation, and mobility planning. The role also offers clear growth paths toward advanced analytics, data engineering, or AI-driven geospatial applications.
