Snapshot
In early 2025, we partnered with a high-profile national property consultancy to scope the migration of dispersed geospatial data and workflows into a central, Postgres-backed GIS environment. The goal was to establish a practical path to a single source of truth, reduce duplication, and standardise day-to-day spatial working practices across multiple rural teams. The engagement produced an organisation-wide workflow map, a Master Data Register (MDR), migration recommendations, and concise “good data practice” guidance to anchor the technical design and change plan.
Challenge
Over time, different rural teams had evolved different ways of working—some primarily in QGIS, some leaning on external web mapping services, others maintaining their own local copies of datasets. While many layers overlapped in purpose, storage locations and update routines didn’t. This created uncertainty about authoritative sources, re-work when outputs conflicted, and a growing backlog of “we’ll tidy that later” technical debt. A one-size-fits-all migration would have failed here; the scoping needed to respect operational realities while converging the organisation on shared standards.
A particular complication was the mix of legacy desktop tooling and region-specific processes. Rather than forcing a big-bang switch, we sequenced recommendations to mitigate delivery risk: document how work is actually done, set pragmatic design conventions, pilot the target approach in a contained slice, and then scale.
Our approach
Discover & map workflows.
We interviewed key users across rural teams to capture how spatial data is sourced, created, checked, and delivered. We visualised the hand-offs and decision points—where GIS touches approvals, reporting, and client deliverables—so that any proposed change could be traced to an operational benefit.
Compile the Master Data Register.
We consolidated commonly used datasets (internal and third-party), their sources, owners, refresh cycles, and whether an authoritative copy already exists centrally. The MDR became the spine of the migration backlog: what to migrate, what to reference live, and what to retire.
Assess central platform fitness.
We evaluated how the existing central database and governance model could serve rural teams: schema patterns (by theme and region), geometry/CRS standards, when to use views or materialised views, and 'permissioning' that’s simple enough to administer while protecting sensitive layers.
Codify “good data practice.”
We produced naming conventions, field design patterns, geometry validation checks, indexing recommendations, and lightweight metadata guidance (provenance, cadence, owner). This enables consistent project templates and predictable query performance.
Plan training & change.
We proposed a champion model, a light skills matrix, and short refreshers focused on the central platform and standardised QGIS project setup—designed to raise awareness of what’s already curated centrally and reduce ad-hoc support demand.
What we delivered
Organisation-wide workflow map for rural teams, showing data entry points, checks, and deliverables.
Master Data Register aligning datasets to those workflows, with clear flags for “migrate”, “consume live”, or “deprecate”.
Migration roadmap with sequenced waves (quick wins first), schema proposals, and standardised QGIS project templates that bind to authoritative tables/views.
Good-practice guide covering naming, CRS/geometry conventions, indexing, views/materialised views usage, and permissioning patterns.
Training & communications plan to embed the standards and drive adoption.
Scoping outcomes
Clarity on the single source of truth. Rural teams can now see which layers are authoritative, which remain external live services, and where local duplicates should be removed.
Standardised project setup. Templates for QGIS reduce per-project configuration, prevent accidental use of stale local files, and point analysts at the right tables and views.
Risk-managed migration path. We avoided a disruptive big bang. Instead, the roadmap starts with well-bounded slices—high-value internal datasets first—before expanding to broader themes and regions.
Immediate housekeeping wins. We identified duplicated layers and outdated copies that can be archived or replaced with centrally referenced sources, cutting noise and re-work.
Targeted upskilling. A champion network and concise refreshers address common gaps (e.g., permissions, editing in a central database, working with views), building confidence and reducing support load.
Rural teams highlights
Internal operational layers: Prioritise migration of frequently edited internal layers (e.g., operational boundaries and works tracking) into dedicated schemas, with region-scoped views to keep day-to-day maps fast and relevant.
Third-party constraints & designations: Keep these as live services where quality and currency are strong; expose them via central views for consistency while avoiding unnecessary duplication.
Project archives: For historic project folders with ad-hoc shapefiles, extract the “authoritative few” that deliver ongoing value, migrate them, and formally archive the rest—reducing clutter and confusion.
Template-first delivery: Provide a standard QGIS project per rural theme/region with pre-bound layers, styling, labelling, and edit rules. This creates repeatability and cuts onboarding time for new starters and seasonal staff.
Pilot then scale: Run pilots on one region/theme to prove the end-to-end pattern (schema + permissions + template + guidance), then replicate with minor variations rather than re-inventing the stack each time.
Skills & tools we used
GIS architecture & data modelling: Schema design in Postgres/PostGIS; strategy for views vs materialised views; permissioning by theme/region; performance-minded indexing.
Esri & QGIS expertise: Standardised QGIS projects that bind to authoritative sources; pragmatic guidance on aligning ArcGIS Pro and QGIS workflows during transition periods.
Data governance & quality: MDR creation; naming and CRS/geometry standards; ownership, refresh cadence, and provenance captured in lightweight metadata.
Change enablement: Champion model, skills assessment, and concise refreshers to embed new patterns without slowing delivery.
Impact & next steps
The client now has a realistic, low-risk path to consolidate geospatial data and standardise rural workflows without disrupting day-to-day delivery. The first migration waves focus on high-value internal layers where the benefits are immediate: reduced duplication, consistent symbology and labelling, and faster access to trustworthy data. Subsequent waves expand coverage by region/theme, guided by the MDR and informed by pilot results.
Critically, the plan balances central governance with local usability. Rural teams retain the flexibility they need, while the organisation gains a clear, auditable system of record. With project templates, shared conventions, and a champion network in place, the migration is set up to deliver measurable efficiency gains and fewer data-related surprises.