ArcGIS Pro Spatial Data Analysis and Mapping Training Course

Course overview

Organisations hold location-rich data in asset registers, customer systems, operational databases, spreadsheets and field surveys, yet many teams cannot turn it into defensible spatial evidence. Analysts need to determine where demand is concentrated, which assets are exposed, how service coverage varies, and whether observed patterns are meaningful rather than coincidental. This ArcGIS Pro course addresses the practical work behind those questions: preparing data, selecting suitable analytical methods, validating results and communicating findings through maps that decision-makers can interpret correctly.

Participants work through ArcGIS Pro workflows for geodatabase design, coordinate systems, data quality assessment, joins and relationships, geoprocessing models, vector and raster analysis, suitability modelling, spatial statistics, network-based accessibility analysis and map production. They learn to choose appropriate tools such as Buffer, Intersect, Spatial Join, Kernel Density, Hot Spot Analysis, Moran’s I, Cost Distance and Network Analyst, and to document assumptions, parameters and limitations. The course also covers Python automation with ArcPy for repeatable analysis and scheduled data-processing tasks.

Instructor-led demonstrations are followed by hands-on labs using realistic operational datasets, including demographic, environmental, infrastructure and service-location data. Participants build an end-to-end spatial analysis project during the two weeks, from source-data assessment to an executive-ready map series and analytical briefing. They leave with a documented ArcGIS Pro project package, reusable ModelBuilder and ArcPy workflows, and a structured method for applying the techniques to their own organisation’s decisions.

The course is designed for GIS professionals, analysts and technical specialists who already use ArcGIS Pro or have equivalent GIS experience and now need to carry out more rigorous spatial analysis, automation and professional cartography.

Course objectives

By the end of this course, participants will be able to:

• Configure an ArcGIS Pro project with appropriate geodatabases, coordinate systems, metadata and data-quality checks
• Apply overlay, proximity, spatial join and network analysis methods to answer operational location questions
• Build weighted suitability models using reclassification, raster algebra, constraint mapping and sensitivity testing
• Run and interpret Moran’s I, Hot Spot Analysis and Kernel Density tools without overstating statistical findings
• Create repeatable geoprocessing workflows in ModelBuilder with validated inputs, parameters and outputs
• Automate ArcGIS Pro data-management and analysis tasks with ArcPy scripts
• Design map series, layouts and symbology that communicate analytical results and uncertainty clearly
• Produce a documented spatial analysis project package containing maps, methods, assumptions and recommendations

Benefits of attending

Target competencies

Who should attend

• GIS Analysts — who need to turn mapped data into repeatable spatial evidence for operational and strategic decisions
• Geospatial Data Scientists — who need ArcGIS Pro methods for spatial statistics, raster modelling and data preparation
• Urban and Regional Planners — who assess development options, service access, land suitability and infrastructure impacts
• Asset and Infrastructure Analysts — who prioritise maintenance, inspections and investment using location-based risk data
• Environmental Analysts — who evaluate habitat, exposure, land-use and environmental monitoring patterns
• Business Intelligence and Data Analysts — who need to add location analysis and decision-ready mapping to organisational reporting

Requirements and prerequisites

Participants should be comfortable navigating ArcGIS Pro, opening projects, adding vector and tabular data, editing basic attributes, and creating simple maps. They should understand common GIS concepts including layers, feature classes, attribute tables, coordinate systems, projections and basic query logic. Experience with Excel or CSV data is useful, as is confidence interpreting charts and summary statistics. Participants need access to a current ArcGIS Pro installation and an account with the required extension licences where applicable. Prior Python programming, advanced statistics, SQL, raster analysis or ModelBuilder experience is not required; these are taught from practical working examples.

Training methodology

Each day combines focused instructor-led ArcGIS Pro demonstrations with guided labs using operational-style datasets. Participants configure projects, run tools, inspect intermediate outputs and compare alternative parameters rather than simply following a click path. Case discussions examine method selection, data limitations and how results can be misinterpreted. Small-group workshops review map design and analytical assumptions. The final two days are organised around an applied project: participants assemble their own documented workflow, receive instructor feedback, and produce an implementation plan for transferring the methods to workplace data and reporting cycles.

Course outline

Day 1: Spatial analysis project foundations

• ArcGIS Pro project structure, catalog organisation and project packages
• File geodatabases, feature datasets and feature class properties
• Coordinate reference systems, transformations and projection choice
• Spatial data types: points, lines, polygons, rasters and tables
• Data provenance, metadata and analytical fitness for purpose
• Attribute validation, null values, domains and coded-value checks
• Map navigation, selection methods and definition queries

Workshop: Participants audit a supplied operational dataset and produce a project data inventory identifying coordinate, completeness and attribute-quality issues.

Day 2: Preparing and integrating spatial data

• Importing CSV, Excel, CAD and shapefile data into geodatabases
• Geocoding addresses and assessing match quality
• Table joins, relates and relationship classes
• Field mapping, Calculate Field and attribute standardisation
• Spatial Join and summary field aggregation
• Dissolve, Merge, Append and multipart feature management
• Topology rules and geometry validation

Workshop: Participants integrate customer, asset and administrative datasets into an analysis-ready geodatabase and document the transformation steps.

Day 3: Vector overlay and proximity analysis

• Buffer design using fixed, variable and geodesic distances
• Clip, Intersect, Union and Identity overlay operations
• Select By Location and spatial relationship predicates
• Near and Generate Near Table proximity measurement
• Erase and symmetrical difference for exclusion analysis
• Summarising exposure and coverage by administrative area
• Choosing resolution and handling boundary effects

Workshop: Participants create an exposure assessment that identifies assets within defined hazard and regulatory buffer zones.

Day 4: Raster analysis and suitability modelling

• Raster properties, cell size, extent and snap raster environments
• Raster conversion and resampling decisions
• Reclassify tools and common measurement scales
• Raster Calculator and Map Algebra expressions
• Euclidean Distance and Cost Distance surfaces
• Weighted Overlay and Weighted Sum suitability methods
• Constraint mapping and sensitivity testing

Workshop: Participants build and test a multi-criteria site suitability model, producing ranked candidate areas and a parameter rationale.

Day 5: Spatial statistics and pattern detection

• Spatial autocorrelation concepts and the modifiable areal unit problem
• Global Moran’s I and interpretation of z-scores and p-values
• Optimized Hot Spot Analysis and incident clustering
• Kernel Density estimation for point-event patterns
• Incremental Spatial Autocorrelation and distance bands
• Outlier Analysis and local spatial relationships
• Communicating statistical confidence and analytical limitations

Workshop: Participants investigate incident data using density and hot spot methods, then prepare a short evidence statement distinguishing pattern from coincidence.

Day 6: Network and accessibility analysis

• Network datasets, travel modes and impedance attributes
• Service Area analysis for coverage measurement
• Closest Facility analysis for assignment decisions
• Origin-Destination Cost Matrix analysis
• Route analysis and operational routing constraints
• Location-Allocation models for facility placement
• Travel-time assumptions, barriers and accessibility equity

Workshop: Participants assess service coverage and recommend candidate facility locations using travel-time-based network analysis.

Day 7: Automation with ModelBuilder and ArcPy

• ModelBuilder interface, variables and connector types
• Creating reusable geoprocessing models
• Iterators, inline variable substitution and model parameters
• Preconditions, validation and error handling in models
• ArcPy scripting structure and geoprocessing environments
• SearchCursor, UpdateCursor and InsertCursor data access
• Script tools, toolboxes and logging repeatable processes

Workshop: Participants convert a multi-step overlay workflow into a parameterised ModelBuilder model and an ArcPy script tool.

Day 8: Advanced mapping and analytical communication

• Thematic mapping choices for rates, counts and indexed values
• Classification methods and class-break justification
• Colour, symbol hierarchy and accessibility-aware design
• Labels, annotation and conflict detection
• Layout design, map surrounds and scale-dependent display
• Map Series and Data Driven Pages replacement workflows
• Export settings for print, PDF and digital distribution

Workshop: Participants create an executive map series that presents analysis results, methods notes and an appropriate visual hierarchy.

Day 9: Applied spatial analysis case workshop

• Framing a spatial decision question and success criteria
• Selecting data sources and evaluating analytical constraints
• Designing an end-to-end geoprocessing workflow
• Parameter selection and scenario comparison
• Quality assurance of intermediate and final outputs
• Documenting assumptions, methods and reproducibility
• Preparing recommendations from spatial evidence

Workshop: Participants begin a capstone analysis case, producing a workflow design, data plan and initial results for instructor review.

Day 10: Capstone presentation and workplace application

• Completing capstone geoprocessing and analytical outputs
• Peer review of method selection and map interpretation
• Packaging projects, toolboxes and data for handover
• Creating analytical briefings for non-GIS decision-makers
• Data governance and version-control considerations
• Identifying workplace automation opportunities
• Building a 90-day ArcGIS Pro application plan

Workshop: Participants present a completed spatial analysis project package containing maps, a reusable workflow and prioritised recommendations for a business scenario.

Tools & standards covered

ArcGIS Pro, ArcGIS Online, ArcGIS Enterprise, ArcPy

A typical training day

08:30 – 10:30	First session
10:30 – 10:45	Refreshment break
10:45 – 12:30	Second session
12:30 – 13:30	Lunch and networking
13:30 – 15:00	Third session
15:00 – 15:15	Refreshment break
15:15 – 16:30	Workshop and daily review

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions