Scope Approximately 32 monitoring tools and 27 datasets Largest dataset - approximately 1,2 million entries Problematic quality assurance 32 data capturing.

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Presentation transcript:

Scope Approximately 32 monitoring tools and 27 datasets Largest dataset - approximately 1,2 million entries Problematic quality assurance 32 data capturing regions, especially deep rural

Challenges of the Old System Thousands of social, demographic, trend, GIS and relational data in various forms and schemas Constant data cleaning, high level of duplication, inconsistent references and orphaned data Data was ed, faxed, sent by pigeon ;)

Enter Third Party Developers Forcing predefined business models onto social data systems – requires a mind shift Third party issues regarding data and loveLife structure – turn around time, quality of backend Technology and Costs –fixed diginet costs, deep rural areas

2006 – Taking control New provincial structures with 9 Provincial Administrators capturing data online Instantaneous access to information and automated reports/graphs via 3G routers 5 Point data Quality Check from site to provincial level Final quality check at national level Site level training Comprehensive monitoring manuals and multi level support Accessible via loveLife VPN, utilising LAN infrastructure; in addition to harnessing the benefits of emerging GPRS, 3G and HSDPA connectivity = huge cost benefit

Development Process Project Definition Workshop Defined objectives, dependencies, assumptions and constraints; functional spec, project scope, prioritised feature lists, design and quality goals, system architecture, logical and physical design Project lifecycle - waterfall approach for each phase – each phase –cyclic approach Forums throughout development: Internal Status Meetings (ISM) Project Status Meetings (PSM) Action and Issue Logs

Technology Visual Studio 2005, JavaScript, AJAX (simplifying navigation) ASP.NET (richer interface) MS SQL Server 2000 Crystal Reports XI Developer Edition dotNet Charting CAN BE DONE WITH OPEN SOURCE

Best Practice Functionality: Avoid Performance Bottlenecks: Client side validation Client side validation Make use of pure html where possible Make use of pure html where possible Page refresh rates Page refresh rates User Ability: Using master pages ensures a consistent look and feel Using master pages ensures a consistent look and feel Required versus operational data Required versus operational dataPerformance: Use stored procedures effectively (code) Security: Roles and Access E.g. administrator versus provincial users Data encryption

The current online database Using CrystalReportViewer object model, logging directly into secure SQL Server Db = interactive reports Display of high performance charting control technologies, aggregating systems with calculation support (.netCHARTING web forms) Displays massive amounts of dynamically generated data on front-end Dynamically generated grid views populated by data sources - created by parameter driven stored procedures Export to Excel, PDF and RTF

Current Challenges Continuous changes around municipal boundaries Census 2001 data not aligned to current boundaries Infrastructure in South Africa Changing Expectations Underreporting – incomplete data sets

Contributions Up to date and extensive GIS coordinate database (public clinics and schools) Infrastructure Volunteer Recognition (Incentives) Accurately linked data Front end Reporting Data as management tool Cost effective

Future Plans Future Plans More sophisticated data analysis Increased number of publications and maps Continual improvement of tools, datasets and database Improved turn around time 100% Quality Continued Maintenance of back ends