Business Intelligence, Predictive Analytics, and Geographic Information Systems

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1 Spatial Intelligence The Intersection of Data Warehousing, Business Intelligence, Predictive Analytics, and Geographic Information Systems 1 GeoAnalytics, Inc. 2008, all rights reserved

2 An Evolving Sensibility Intelligence Understanding Knowledge Information 2 Data

3 Organizations must evolve from What We Think to What We Know. Gary Lovemann, CEO Harrah s Entertainment 3

4 The Information Evolution Model Adapted d from: The Information Revolution, Davis et. al, 2006 Innovation Enterprise Intelligence and Analytics to 5 Create New Value Optimization 4 Enterprise Information and Analytics to Create Efficiency Integration Consolidation 2 3 Enterprise Infrastructure to Enable Knowledge Management Workgroup Data and Analysis Us Versus Them Operational 1 Individual Data and Analysis the Information Maverick 4

5 Key Concepts Knowledge Management Knowledge Management is a conscious strategy t of getting the right knowledge to the right people at the right time O Dell ODell, Grayson, If Only We Knew What We Know: The Transfer of Internal Knowledge and Best Practice, 1998 How an organization manages knowledge is a fairly good predictor of both best practice and organizational success 5

6 Key Concepts Business Intelligence and Analytic Intelligence Business Intelligence is the use of information that t 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 6

7 7 IDC s Business Analytics Taxonomy, 2007

8 Technology/Solution Providers SAS Institute Teradata SAP/Business Objects IBM/Cognos Oracle/Hyperion Microsoft Information Builders 8 Others..

9 Business and Analytic Intelligence Platform

10 Location is Integral to Knowledge Management and Intelligence Outcomes and Performance are inherently geographic whether localized, regional, or global Events rarely occur in a vacuum They affect surrounding people, economic and natural ecosystems, institutions, i i and communities i (Predicting where things will happen is powerful) 10

11 Everything is related to everything else, but near things are more related than distant things Waldo Tobler On understanding the science of location and geography 11

12 Key Concepts Spatial Analytics Spatial analytics and geographics is the science of location, adjacency, and direction between physical and cultural features on the landscape Proximity analysis Network analysis Buffer analysis Cluster analysis Gravity modeling 12

13 Synergy of Traditional and Spatial Analytics Traditional Analytics Spatial Analytics Financial i Analysis Regression Operations Research Correlation Market Analysis Predictive Modeling Scorecarding Database Spatial Database Geocoding Network Analysis Spatial Regression Cluster Analysis Buffer Analysis Auto Correlation Hotspot Analysis

14 Key Concepts Spatial Intelligence Spatial Intelligence is the fusion of analytical lti l GIS, Business Intelligence and Predictive Intelligence Builds on descriptive analytics Provides the context for inferential analytics Spatial Intelligence adds the geographic dimension to data management, analytics, and visualization 14

15 Spatial Intelligence in a Commercial Organization Spatial intelligence and predictive analytics can be integral to corporate strategies for: Growth Enhanced profitability in core business areas Delivering needed products and services to customers conveniently and affordably Providing a competitive i advantage 15

16 IDC s Business Analytics Taxonomy, 2007 An Evolving Perspective Spatial Analytics and Visualization Data access, cleansing, enhancement, intelligent storage, analytics and presentation 16

17 Enterprise Spatial Intelligence Platform BUSINESS AND VALUE ADDED DATA SOURCES MASTER DATA MANAGEMENT SOA / XML TRADITIONAL AND SPATIAL ANALYTICS PRESENTATION VISUALIZATION SOURCE 1 Spatial Internal SOURCE 2 Spatial Internal SOURCE 3 Spatial External Non- Spatial Non- Spatial Non- Spatial ETL NON-SPATIAL Data: Access Assessment Cleanse Quality Enhancement Transformation SPATIAL Data Repository Dimensional Data Stores Data Marts Data Marts TRADITIONAL Statistics Econometrics Operations Research Forecasting SPATIAL Autocorrelation Interpolation Hotspot Analysis Regression Gravity Modeling Cluster Analysis Dashboards Reports Data / Application Services OLAP Metadata

18 Orange County, FL EAS Output Architecture

19 Orange County, FL EAS Output Architecture

20 Data Flow Management (ETL) Non-spatial Spatial

21 Orange County, FL EAS Output Architecture

22 Orange County, FL EAS Output Architecture

23 Orange County, FL Address System Architecture

24 24 Enhanced Information Visualization From lists to tables to cubes to charts to maps

25 Synergy of Traditional and Spatial Analytics Spatial Intelligence Financial i Analysis Regression Operations Research Correlation Market Analysis Predictive Modeling Scorecarding Geocoding Network Analysis Spatial Regression Cluster Analysis Buffer Analysis Auto Correlation Hotspot Analysis Database Spatial Database Business Intelligence Predictive Intelligence Risk Analysis Decision Support Performance Management

26 Spatial Intelligence in Mobile Asset Management Optimization Distance vs. Time vs. Priority Qualification Cost Fleet Management Model and optimize maintenance Model and optimize life-cycle costs and benefits

27 Spatial Intelligence in Retail Market forecasting and management Target store sales predictions Competition gravity modeling Sales territory modeling/resource prioritization Supply chain modeling and optimization Store layout and product placement Customer analytics (recruit, retain, value mgmt, etc.) 27

28 Intelligence in Gaming Integrated Gaming Repository & Analytic Platform ENGINES Recruitment & Customer Lifetime Value Relationship Re-Engagement Churn Identification & Acquisition Engine Optimization Engine Cementing Engine Engine Minimization Engine CONTENT AND INTELLIGENCE Operational Dashboard Web Service Data Feeds 28

29 29 Spatial Intelligence in Gaming

30 Consumers Data Inputs Casino Exec Casino Analyst C C Discovery Browse & Query Analysis Spatially-enabled GAMECenter Business Services (Portal) Business Intelligence/Reporting ti Analytical Modeling Solution Modules A Analyst Transaction Data Customer Data ATM P Casino IT C Demographic Data SP Customer Database Casino Client System Marketing Analyst SP Marketing Database Service Providers M Data Manager Data Mart Data Mart External Publication Custom Data Marts Data Management Publication Staging Gaming Customer Data Mart Data Mart M Data Manager Extract, Transform, Load, And Georeference Data NCOA Data Other Data Providers Gaming Data Customer Data Casino Client P

31 31 Spatial Intelligence in Disease Detection

32 Strategic Alignment and Execution Adapted From: The Strategy Focused Organization, Kaplan and Norton, 2001 Mission Why we exist Core Values What we believe in Vision What we want to be Strategy Our game plan Gauging Results Implementation and focus Tactics What we need to do Personal Objectives What I need to do Strategic Outcomes Business Case Principles Objective Mechanisms Measures of Success (KPI s) Tasks Individual Objectives and Actions Delighted Customers Effective e Processes 32 Motivated Workforce

33 Spatial Intelligence Performance Management and KPI s Key Indicators Roadside Maintenance Customer Satisfaction Roadside Debris Pick-Up Customer Satisfaction Surface Maintenance Customer Satisfaction Roadside Signage Customer Satisfaction Responsiveness Customer Satisfaction Customer Satisfaction Roadside Maintenance Project Completion: Dist. 58 Surface Maintenance Cost per Mile Roadside Signage Customer Satisfaction by District Cost by District Customer Satisfaction by Parish Spend by House District

34 Integration Points for Spatial and DW-BI-PA Platforms Visualization INTRANET INTERNET Map Servers/Services General purpose viewer Vertical templates Portlets (for dashboards) ESRI ArcIMS ESRI ArcGIS OGC WMS Google KML Proximity Analysis Cluster Analysis Analytics Spatial Statisticsti ti Geoprocessing Network Analysis Buffer Analysis Spatial Analysis Services ESRI ArcGIS Server Oracle Spatial Func DW Datasets Master Data Management Spatial Data Access Web Data Services Spatial Datasets Spatial Data Services ESRI GDB ArcSDE Oracle Spatial DB ESRI ArcData Services

35 Enterprise Spatial Intelligence Organizational Considerations Process, Project & Operational Management Governance, Partnerships & Collaboration Vision, i Strategy, t & Performance Management Technology & Data Systems Management Sustainability & Change Management 35

36 Management and Control Management Models Centralized versus decentralized Support Service Delivery Options Business Unit (e.g. Market Planning, Logistics) Service department (IT/GIS) Executive office (CFO, CEO) 36 Considerations Budget autonomy and power Visibility Impartiality

37 Contact Information GEOANALYTICS, INC. Pt Peter Thum President GEOANALYTICS.COMCOM 37

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