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DAS offers the power of Geomatics and location-based analysis

DAS, powered by Statistics Canada, offers a framework for data analysts and scientists to access and leverage trusted geospatial data and tools in the Geospatial Analytics Environment (GAE). These secure cloud-based services offer many advantages.

  • Choose from easy-to-access open-source and ESRI GIS software.

  • Explore, analyze, and, develop insights about your geospatial data.

  • Create geo-enabled statistical data for analytics and visualization.

  • Create statistical models which incorporate geospatial data.

  • Integrate geospatial data to collaborate and share across DAS.

  • Create and share compelling geospatial visuals and stories.

Data storage

Manage, edit, share and backup

A fully managed database engine that handles management functions such as upgrading, patching, backups, and monitoring without user involvement. PostGIS adds support for geographic objects allowing location queries to be run in SQL.

This solution for raster image storage or sharing data files includes object, file, disk, queue, and table storage. There are also services for hybrid storage solutions, and services to transfer, share, and back up data.

Geospatial analysis, visualization, and sharing

Analyze, share insights and tell data stories

High-performance virtual machines are configured for Geospatial processes, utilizing GPUs and large-memory banks for advanced spatial operations.

A full-featured, user-friendly desktop GIS application that supports raster, vector, and database systems to view, edit and analyze spatial data.

Analyze geospatial data, create and visualize maps and share results to ArcGIS Enterprise using ArcGIS Pro (license required).

Collaboration and flexibility are central to ArcGIS Enterprise, allowing you to organize and share your work. Interactive and easy-to-read data visualizations including, map-centric apps, stories, dashboards, can be created using a no-code app builder.

Use ArcGIS Insights for exploratory analysis to uncover patterns and relationships through a drag and drop interface. It integrates spatial and tabular analysis not only with maps, but also with tables and charts.

Write, test, and debug your geospatial analysis code with RStudio, Jupyter, PyCharm or VSCode. Flexible interfaces allow users to configure and arrange workflows and models for data science, scientific computing, and machine learning.

Data Analytics Services

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