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Common GIS Job Tools

Every GIS shop has a different stack, but most pull from the same pool of tools. This page is a cheat-sheet of what's actually used — desktop, web, code, data, and infrastructure.


Desktop GIS

Tool Use Notes
ArcGIS Pro Industry standard for analysis, cartography, sharing Subscription
QGIS Free, open-source equivalent Heavily used in academia and Europe
ArcMap Legacy desktop GIS Retired by Esri; still in some shops
Global Mapper Lidar, terrain, niche analysis Common in surveying / engineering

If you only learn one, learn ArcGIS Pro. If you learn two, add QGIS.


Web GIS / cloud

Tool Use
ArcGIS Online Hosted maps, dashboards, apps, story maps
ArcGIS Enterprise Self-hosted Esri stack (Portal, Server, Data Store)
ArcGIS Hub Public-facing community sites
ArcGIS Experience Builder Configurable web apps
Mapbox Custom web maps with vector tiles
Maptiler Hosted vector tiles
CARTO Hosted spatial database + apps
Felt Modern collaborative mapping

→ See ArcGIS Online roadmap.


Programming

Language Used for
Python (arcpy, pandas, geopandas, shapely, rasterio) Automation, ETL, analysis
SQL (Postgres/PostGIS, SQL Server, ArcGIS file gdb) Data queries, joins, spatial SQL
R (sf, terra, tmap) Statistics-heavy spatial analysis
JavaScript (ArcGIS Maps SDK, Leaflet, Mapbox GL, OpenLayers) Web maps and apps
Bash / PowerShell Scripting deployments

→ See Python for GIS, SQL for GIS.


Spatial databases

Database Notes
PostgreSQL + PostGIS The de-facto open-source spatial database
SQL Server + Spatial Common in government and enterprise
Oracle Spatial Used in some utility / federal stacks
SpatiaLite Spatial extension for SQLite
DuckDB + spatial Modern in-memory analytics
BigQuery / Snowflake / Redshift Cloud DWHs for big spatial data

Geodata formats

Format Use
Shapefile (.shp) Legacy but ubiquitous
File geodatabase (.gdb) Esri standard, multi-feature
GeoPackage (.gpkg) Modern open standard
GeoJSON Web-friendly text format
CSV with WKT/lat-long Tabular interchange
KML/KMZ Google Earth
GeoTIFF Standard raster
COG (Cloud-Optimized GeoTIFF) Cloud raster
LAS / LAZ Lidar
NetCDF Climate / scientific

ETL / pipelines

Tool Use
FME Industry-leading ETL for spatial data
GDAL/OGR (ogr2ogr) Free format conversions and reprojections
ArcGIS ModelBuilder Visual workflow inside Pro
arcpy / Notebooks Scripted automation
Apache Airflow / Prefect Schedule production ETL

Data visualization (beyond maps)

Tool Use
Power BI Common enterprise dashboarding (has a maps integration)
Tableau Strong with non-spatial data + maps
Kepler.gl Stunning point-cloud and large dataset viz
Looker Enterprise dashboards
Plotly / Dash Custom Python dashboards

Imagery & remote sensing

Tool Use
ENVI Full-featured RS suite
eCognition Object-based image analysis
Google Earth Engine Petabyte-scale RS in the browser
Sentinel Hub Streamed satellite imagery
Pix4D / Agisoft Metashape Drone / photogrammetry
arcpy.ia + Image Analyst RS inside ArcGIS Pro

CAD / surveying / drones

Tool Use
AutoCAD / Civil 3D Common in engineering shops
Trimble Business Center Survey processing
DJI Terra / Pix4D Drone processing
3D Mapping Solutions Mobile mapping

Documentation, version control, collaboration

Tool Use
Git + GitHub Version control for code, data, docs
Jupyter / VS Code Notebooks and editor
Markdown Documentation
MkDocs / Sphinx / Quarto Static site generators
Notion / Confluence Internal team docs

Common data sources you'll touch

Source What you get
US Census / ACS Population, demographics by tract / block group
TIGER/Line Boundaries, roads, water, places
OpenStreetMap (OSM) Global roads, POIs, buildings
USGS NHD / WBD / 3DEP Hydrography and elevation
NLCD Land cover for the US
NOAA / NWS Weather, hazards, climate
USDA NASS / Cropland Data Layer Agriculture
FEMA NRI / NFHL Hazards / flood zones
Esri Living Atlas Curated authoritative layers
GADM / Natural Earth Global boundaries
GTFS Public transit

→ Full list with links: Resources.


Cloud

Provider Common GIS-relevant services
AWS S3 (data), EC2, RDS Postgres, Lambda, OpenSearch
Azure Blob Storage, Postgres, App Service, ArcGIS Enterprise
GCP BigQuery, Cloud Storage, Earth Engine

For most analyst roles you don't need deep cloud expertise — but knowing how to read from S3 or run a script in a VM is increasingly common.


"Bonus" specialty tools

Tool Niche
Network Analyst extension Routing, OD matrices
Spatial Analyst extension Raster analysis
3D Analyst / CityEngine 3D visualization
Survey123 / Field Maps Mobile data collection
Workforce / QuickCapture Field operations
Insights for ArcGIS Quick exploratory analysis

What to actually learn first

If you're starting from zero, here's the prioritized stack:

flowchart TD
    A[ArcGIS Pro]:::core --> B[ArcGIS Online + Story Maps + Dashboards]:::core
    A --> C[SQL: WHERE, joins, IN, LIKE]:::core
    B --> D[QGIS as alt]:::nice
    C --> E[Python: arcpy + pandas]:::core
    E --> F[geopandas + shapely]:::nice
    A --> G[Cartography & layout]:::core
    F --> H[PostGIS]:::nice
    E --> I[Git + GitHub]:::nice

    classDef core fill:#dbeafe,stroke:#2563eb,color:#1e3a8a
    classDef nice fill:#fefce8,stroke:#eab308,color:#854d0e

Blue = required first. Yellow = strong "next layer."


→ Final section: Resources.