In order to answer this question, the National Petroleum Council developed an analytic data warehouse using Oracle relational and OLAP technology. Implemented by Vlamis Consulting, the NPC report states:You can find more on the Vlamis blog here (Vlamis Software » Blog Archive » Vlamis Used Oracle OLAP For National Petroleum Council Study)
The data warehouse was designed to be the main analytical tool for the Task Groups, accepting all data collected from the survey questionnaire and other data sources. As the survey data were multi-dimensional, Oracle OLAP database technology was used and the collection was organized using 7 dimensions:The statistics contained in the report posed interesting technical challenges, including non-additive data, skip-level hierarchies, non-standard aggregation rules, and more - all of which Oracle OLAP is designed to manage. Discoverer OLAP was used to analyze the data.
1. Time (year)
2. Geography (country or geographic region)
3. Energy type (e.g., Oil, Gas, Coal, Nuclear, Renewable)
4. Energy sector (e.g., Commercial, Residential)
5. Case type (e.g., Business as usual, Alternative energy policy)
6. Units (applicable unit of measure)
7. Source (e.g., Public, Proprietary)
Thanks to Marty Gubar from OLAP Product Management for passing this on.