Siva Ravada
Senior Director of Development, Oracle Spatial

 

Siva Ravada is Senior Director of Development for Oracle’s Spatial technologies. Ravada joined Oracle in 1997, after receiving a Ph.D. in Computer Science from the University of Minnesota, with a specialty in Spatial Technology for High Performance GIS Computing Environments. Siva is one of the founding members of the development of Spatial technologies in Oracle. He currently manages the Spatial and MapViewer development teams. He holds numerous patents and has several publications in peer reviewed journals and conferences.

Using Location Analysis in Large Scale Operational Systems

The effectiveness of most business applications and operational systems can be enhanced by exploiting the 2D vector, raster processing, and MapViewer features that are part of Oracle’s spatial technologies. Learn how to use these capabilities as part of the standard database, Java middleware, and web services frameworks that comprise most commercial applications. Using code examples, we will describe how real world applicationscan benefit from location analysis, including examples from insurance, business geographics, and business intelligence applications.

How to Build a Better GIS Application

Dr. Siva Ravada, Senior Director, Software Development

By using in-database spatial analytics, Oracle Database simplifies the development of better GIS applications and makes it possible to manage larger, more detailed datasets with unsurpassed performance.  We will describe a land management application that is built using Oracle's spatial technologies. We will show examples of complex spatial analysis queries in the database to solve common problems encountered in GIS applications. These include splitting and shifting geometries along land parcel boundaries and updating specific vertices of a geometry based on spatial analysis.   We also show how spatial functions in the database are used to create new spatial features based on application logic.   Topics covered include Oracle Spatial and Graph 2D vector analysis features and network data model.