1. Building a Better Mousetrap (Smarter)

2. Introduction Background The Challenge Our Approach Why build models Thoughts

3. Background OMNILINK 25 + yrs Spatial Systems Service Highly specialised Not an SDLC company But have software products

4. AssetWhere AM FM Tool for Schools 80 Customer Organisations Grew from Ms Access Then SQLSERVER, MapInfo (TAB files) ‘Most’ of the data replicated Hybrid Database/Proprietary Mapping MapInfo Plugins (end of life) Visual Basic Drives a Service Business Focus of the business is the spatial data service not software

5. AssetWhere

6. The Challenge Technical Most or all components end of life Desktop only Multiple/Redundant Data Sources Missing constraints No internal product knowledge

7. Challenge Data 80 Customers Data not necessarily consistent Resources 1 Dev 4 Expert Users and Consultants No technical documentation, no source code. No Real access to the customer (Culture)

8. Our Approach Build a sound foundation using independent standards Model Use cases RDBMS SQLSERVER Spatial

9. Use Case Model

10. Data Model Convert MapInfo directly to SQLSERVER Using EA, reverse Engineer the RDBMS Data Model (s) Visually created merged, clean and properly structured Model. Little a time

11. Slice by Slice

12. Rooms

13. Results Complete rebuild of AssetWhere 14 Mths (Me and guy) Runs across all platforms HTML 5, OGC Flexible, Robust Platform Ready for SAAS SAML, SAOML, etc OMNILINK’s development completely changed Thrown away the spreadsheets Agile but pragmatic

14. Thoughts, Learning Generating DB from the Model saved massive amounts of time. Solve most issues in the model rather than in coding Visualisation Saves Time. Communicating both the requirements and the solution was simplified. Modelling supports streamed development

15. Summary 1:10:100 Solving in the Model Save Time Building analogy. Only when digging stops does the building go up The Highlander Rule The Devil is in the Data