1. Spatial Intelligence – New ideas for Integrating GIS Across the Enterprise © GeoAnalytics, Inc. 2008, all rights reserved

2. A Strategic Direction Data Information Knowledge Understanding Intelligence

3. Key Concepts – Business Intelligence and Analytic Intelligence Business intelligence is the use of information that enables organizations to best decide, measure, manage and optimize performance to achieve efficiency and financial benefit ( Gartner Business Intelligence Summit 2007 ) Analytic (Predictive) Intelligence builds on previous experience, metrics, relevant variables, and circumstances to model future outcomes

4. Key Concepts – Spatial Intelligence Spatially Enabled Business and Predictive Intelligence adds the geographic dimension to analytics and visualization Spatial Intelligence Brings: –Context –Understanding –Coherency

5. Key Concepts – Spatial Intelligence Spatially Enabled Business Intelligence and Predictive Intelligence is about strategic alignment to create outcomes, not just outputs Organizations must evolve from “what we think” to “what we know”

6. ANALYTICS Business Intelligence Analytical Intelligence Risk Analysis Decision Support Performance Management Spatial Non-Spatial SOURCE 1 Spatial Non-Spatial SOURCE 2 Spatial Non-Spatial SOURCE 3 Metadata Intersection of Intelligence and GIS Reports Dash Boards Data and Application Services DataMarts DataMarts Dimensional Data Stores DataRepository ETL Profiling Access Quality Enrichment SOA / XML Monitoring

7. Managing Data Quality Monitor & Manage Profile & Quantify Cleanse,Validate,Improve Integrate & Organize Enrich & Value Add EnterpriseData Master Data Management Adapted from DataFlux®

8. Technology to Manage Data Quality

9. Traditional Analytics Spatial Analytics Traditional Analytics Spatial Analytics Spatial Database DatabaseDatabase AddressValidationAddressValidation Cluster ClusterAnalysis Analysis Forecasting ForecastingAnalysis Analysis Network Analysis Predictive PredictiveLocation Location GeocodingGeocoding Buffer BufferAnalysis Analysis Financial FinancialAnalysis Analysis Predictive PredictiveAnalysis Analysis Regression Regression ScorecardingScorecarding Operations Research Operations Research IT Value Management StatisticalStatistical The Intersection of Traditional and Spatial Analytics

11. So Why Is This Important?

12. Public Health Information Network

13. Public Health Information Network: OLAP – Asthma Data Cube

14. Public Health Information Network: OLAP – Asthma Data Cube Bar Chart

15. Public Health Information Network: OLAP and GIS Integration

18. Sample Data Public Health

19. Sample Data Public Health

20. Bureau of Land Management Human Resource and Financial Management Spatial Intelligence

21. Human Resources at BLM Source: BLM and SAS

22. Centers For Disease Control and Prevention Health Situational Awareness

23. U.S. Department of Health and Human Services Centers For Disease Control and Prevention Goal: To enable health situational awareness through access to existing data from healthcare organizations across the country. Source: SAS

24. Region Selection U.S. Department of Health and Human Services Centers For Disease Control BioSense Home Page Source: SAS

25. BioSense Health Indicators Page Syndrome-Specific Maps Source: SAS

26. Drill-Down Layers Lab Orders And Test Results BioSense Display of Laboratory Data Source: SAS

27. City of Charlotte-Mecklenburg County, North Carolina Environmental Data Management System

28. City of Charlotte-Mecklenburg County

32. Conclusion New ways of managing information and making use of data Spatial as a key component to OLAP Distributed storage models

33. GeoAnalytics, Inc.

34. Contact Information GEOANALYTICS, INC. David Mockert Director of State and Local Practice dmockert@geoanalytics.com GEOANALYTICS.COM