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A presentation conducted by Dr Rohan Wickramasuriya, SMART Infrastructure Facility, University of Wollongong. Presented on Tuesday the 1st of October 2013. Business Intelligence (BI) has popularly been adopted as a process that enables easy access, analysis and visualization of information through specialized set of tools for informed decision making. Two most noticeable characteristics of traditional BI is that it (a) is largely used in single-organization environments and (b) uses predominantly aspatial data. We believe that BI has applications beyond single-organization environments, but it very much requires integration of geospatial capabilities given the increasing availability of large volumes of spatial data and a growing interest to see things spatial. The SMART Infrastructure Dashboard (SID), our innovative solution that fuses BI and Geographic Information Systems (GIS), fills this significant gap. In this study, we demonstrate how SID can be used to perform spatio-temporal analysis and visualization of diverse sets of data to uncover complex interrelationships among utility usage, demographics and weather patterns at local and regional scale.
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Monday, 30th September 2013: Business & policy Dialogue
Tuesday 1 October to Thursday, 3rd October: Academic and Policy Dialogue
www.isngi.org
ENDORSING PARTNERS
The following are confirmed contributors to the business and policy dialogue in Sydney:
• Rick Sawers (National Australia Bank)
• Nick Greiner (Chairman (Infrastructure NSW)
www.isngi.org
SMART Infrastructure Dashboard
Presented by: Dr Rohan Wickramasuriya, SMART Infrastructure Facility, University of Wollongong
SMART Infrastructure Dashboard
Rohan Wickramasuriya
Outline
• Background & Problem • Potential solution – pieces of the jigsaw • SID – assembled jigsaw Study area, stakeholders and data Technical architecture and workflows SID in action
• Conclusion and future works
• Many utility service providers
• Where’s the problem? holistic view? integrated planning? how can I take actions?
• Difficult challenge multiple stakeholders dispersed datasets diverse formats (data) data complexity
Why BI? ability to handle diverse & complex data optimized data storage for fast query performance slice & dice, drill down, roll up captivating, easy-to-understand reports online access
• Business Intelligence (BI) people
processes
technology
Access Analyse
Data
Knowledge
• Geographic Information Systems (GIS)
Why GIS? infrastructure data largely spatial map is a better visual
Public Infrastructure
Domain
Regional focus SQL driven No complex modelling
• The Illawarra region • 5 Councils • Infrastructure service provision diverse providers private & public
• Electricity distribution 1 company
Endeavour Energy
• Water & Sewage networks 3 operators
Sydney Water
• Solid Waste 4 operators
REMONDIS
Provider Data type Temporal Resolution
Spatial Resolution
Endeavour Elec. Consumption Geom. network
Monthly N/A
SA1
Sydney Water
Water consumption Water quality Water demand Discharge volumes Power consumption Geom. network – water Geom. network – sewage
Quarterly Monthly Daily Daily Monthly N/A N/A
Postcode Reservoirs (point) Reservoir zone
REMONDIS Waste volume & weight Collection Routes
Daily Collection Route
ABS Demographic Yearly SA1
BOM Rainfall, Temperature Daily Station
Electricity
Data Sets
Water
Waste
Demographic Data
Weather Data
Data Staging & Warehousing
Staging Database
Data Warehouse
Geo-BI Analytics
Analytical Reports
Interactive Dashboards
End Users
Web Interface
ETL
Metadata Repository
• Software Pentaho Data Integration PostgreSQL/PostGIS Yellowfin
• Why star schema? simple queries fast query performance easy to understand
• What is star schema?
Schema 1 Schema 2 (network) Common dimensions
• Spatial hierarchy SA4 - SA1
• Temporal hierarchy year - season/quarter - month - week - day
Seeing is believing
Conclusion
• Right people, data, fusion of BI & GIS (processes & technologies) can provide the integrated vision required for regional infrastructure governance
• SMART Infrastructure Dashboard – a proven demonstrator that can be replicated elsewhere
• Happy to transfer knowledge & technology • Future work Automating spatial data handling – FME & Geotools/ArcGIS for Server Network interdependency
Prof. Pascal Perez Research Director, SMART Infrastructure Facility [email protected]
