GIS Automation and Geospatial Databases

We configure databases for storing, querying and updating geographic information among authorized users.

• Corporate Spatial Database

  Geographic data are dispersed and cannot be queried by multiple users.

  Expected deliverables: Indexed PostGIS schema with SQL DDL definitions and a PostgreSQL dump; verified spatial views in SQL with a GPKG export; spatial-integrity and backup log in MD and CSV with SHA-256 checksums.

• Technical Review of Spatial Database Schema and Indexes

  Review the database schema and slow-running queries in a growing PostGIS database.

  Expected deliverables: Table, CRS and index inventory, with documented optimization proposals.

• Spatial SQL Views for Recurring Queries

  Create a repeatable query for polygons and their attributes.

  Expected deliverables: Versioned SQL views or queries, GIS output and validation plan.

We prepare portable geographic files and databases for querying, exchange and offline work.

• Optimized Interoperable Spatial Data Package

  Exchange large spatial datasets efficiently.

  Expected deliverables: Interoperable GeoParquet dataset with JSON metadata; report on potential losses during columnar conversion in CSV or MD, including hashes.

• Portable, Queryable Offline Spatial Database

  Geographic information needs to be circulated offline.

  Expected deliverables: Indexed SpatiaLite geodatabase in SQLite/SpatiaLite with SQL queries; server-independent spatial SQL extract in GPKG accompanied by SQL.

We combine data from different sources and configure queries to locate, link and extract records.

• SQL Integration of Large Territorial Datasets

  Repeated joins of tables and geometries.

  Expected deliverables: Geospatial analytical table in GeoParquet with SQL queries; geometry-based aggregation summary in CSV or GPKG.

• Joining External Tables and Layers by a Verified Key

  Business tables and geometries share an ID and need to be combined.

  Expected deliverables: Joined layer, unmatched-record matrix and key schema.

• Field and Data Type Migration Between GIS Versions

  A database schema has changed; older deliveries must be converted to the new schema.

  Expected deliverables: Source-to-target field map, migrated files and data-loss report.

We carry out repeatable operations across multiple files, reducing manual intervention and documenting results.

• Repeatable Batch Geospatial Processing

  Many files need the same transformation.

  Expected deliverables: Python batch-geoprocessing pipeline in PY files, including requirements and GPKG outputs; comparison of spatial overlays in GPKG or CSV; processing performance report in CSV or MD.

We create automated sequences for data transformation, analysis and cartographic document generation.

• Reproducible Basic Geoprocessing Template

  Repeat documented GIS operations.

  Expected deliverables: Graphical geoprocessing model, test data and parameter log.

• Automated Generation of Maps and GIS Packages

  Recurring deliverables take too many hours.

  Expected deliverables: Reproducible PyQGIS script in PY with requirements and a QGZ project; automated GIS outputs in GPKG, PDF or SVG with a manifest; GIS execution record in CSV or JSON with logs.

• Map Template with Reusable Variables

  Dozens of similar reports need updated data without rebuilding the layout.

  Expected deliverables: QGZ template, parameterized layout, samples and parameter sheet.

• Transferable QGIS Project with Verified Paths and Styles

  A third party must open the same layers, symbology and layout.

  Expected deliverables: QGZ project, file structure, manifest and relative-path check.

We inspect database structures, relationships and consistency, recording any detected issues.

• Reproducible Log of Geographic Transformations

  Provide a record of the operations that produced a derived file.

  Expected deliverables: Sequential record of algorithms, versions, parameters, hashes and outputs.

• Change Report for Recurring Data Deliveries

  Compare monthly data packages to identify changes in records and structure.

  Expected deliverables: Feature and schema changes, detected causes and comparison evidence.