Mapping GIS to Enterprise Architecture and Analytics


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Mapping GIS to Enterprise Architecture and Analytics

  1. 1. Mapping Geospatially Enabled Systems to Enterprise Architecture and Analytics Dennis Crow, Ph.D, PMP
  2. 2. Mapping Geospatially Enabled Systems to Enterprise Architecture and Analytics “Analytics” and “Geographic Information Systems” are ubiquitous terms now. There are innumerable geo-enabled applications and location-based services Where does Enterprise Geospatial Architecture fit into that picture? Finding Enterprise Architecture on a map always seems difficult
  3. 3. Thinking about using GIS should begin with the notion of “geospatially enabled” systems or analyticcs, not with implementing “GIS.” This is not just a sofware or application development process, but a process of providing information and analysis that is applicable to and needed by different audiences. Geospatially enabled data and systems must be flexible to use with many other approaches to Business Intelligence and Analytics as well as plain old statistics, and unique geospatial statistical operations. Enterprise View of Geographic Information Systems Organizations contemplating using Geographic Information Systems need an enterprise architecture that puts geospatial data, applications, and analytics within the total context of software development and data management as well as coordinates among all groups involved in standing up and maintaining geospatially enabled systems. All common processes and standards must be applied to geospatially enabled systems. Geospatial data and applications should not be regarded as ancillary to others or as exclusive from all other standards for data management and metadata. A Roadmap covers all geospatially enabled systems, not just selective or “special” applications and is a foundation for future infrastructure changes and analytical needs.
  4. 4. Enterprise Architecture sets the Stage for Geo-enabled Analytics Geospatial Application Development Geospatial Master Data Cartographic Data, Crops, Facilities, Watersheds, Census Data, and geospatial web services or SOA for geospatial master data Geospatial Master Data Production Imagery, Raster, Vector (Aerial Photos, Thermal spectrum, Streets, Water bodies, Political Boundaries) Charts, graphs, maps associated with other business data Information Standards Geoprocessing, geocoding, modeling, data capture, etc. Business Intelligence Geospatial Functional Services Target Architecture Enterprise Architecture Data Creation, Systems Integration, Information Dissemination, Functional Implementation, Geospatial Data Warehouse, Geospatial Processing as a Service
  5. 5. Data and Technology Patterns Separated but Coordinated for Different Analytic Purposes Planning and Analysis Geospatial Data Application Organization Implementation and Production Business Intelligence Solutions Public Facing Channels Direct Customer Interaction Lines of Business Program Implementation Budget, Performance, and Policy Analysis Business Analysis, Development Requirements Analysis Geospatial Master Data, Services, Data, Information Analysis and System Data Production, EA Analysis Integration, Management, Services Project Analysis Multi-Channel Provisioning, Distribution, and Testing Exchange Hosting, Cloud Enterprise Information Management, Analytics Geospatial Analytics Communication with Lines of Business, Staff, Analytic Community, Customers, Other Groups
  6. 6. External Providers Organization Staff Architecture Data Metadata Systems Should Be the Foundation Enterprise Architects Data Providers Federated Geospatial Data General Public Application Developers Business Offices Distributed data and resources Enterprise Data Warehouse (Analytic) Geospatial Master Data and Services (Analytic) Solution Architects Customers That serves your community Reseachers Data Architects
  7. 7. Business Systems Datastores Data Warehouses and Data Stores Provide and Consume Data Needed to Geospatially Enable Information Geospatial Master Data Provides a Geographic Context and Receives Data from Other Gesopatially Enabled Sources and Services Other Pubic-facing Applications Customer Matching Master Data Datastore Distributed data and resources Enterprise Data Warehouse (Analytic) Tables Geospatial Master Data and Services (Analytic) “Layers” Transaction Systems Analytics Datastore Other Analytical Datastores Other External Serving Datastores Exterma; Datastore and Processing Services Internal Data and Services
  8. 8. Analytics are only as good as the geospatial data produced and maintained from authoritative sources and metadata Source: U.S. Federal Geographic Data Committee Geospatial Data Life Cycle
  9. 9. Information Shared with Performance Assessment Community becomes Feedback for Improvements Information needed to analyze program performance against desired or required metrics Geospatial Data Becomes Part of the Information Stream IT Facilitation Operational Business Sponsors Strategic Decision Makers Data Applications Business Analyst Business Expert GIS Budget Analyists Business Data Testing Architecture Business Rules Policy Analyst Business Analyst Feed back on Outcomes of Program Performance based on metrics to Business Information Return to Business Researcher Analyses based on business data or data provided to other sources Analysis and data shape program budget and IT investment decisions Information about performance output of programs
  10. 10. Geo-enabled applications are likely to use distributed and coordinated geospatial data and business data that is flexible for multiple audiences and multiple channels. Dash Boards Enterprise Reporting Geospatial Analysis Statistical Analysis Data Visualizatio n Business Data Master Geospatial Data Hub Geospatial Data Data Mining
  11. 11. Mapping Geospatially Enabled Systems to Enterprise Architecture and Analytics Dennis Crow, Ph.D, PMP