Chapter 1. Beyond reporting: business analytics
Figure 1.1. Mondrian is the analytics engine for the business application.
Figure 1.2. Orders by city
Figure 1.3. Orders by customer
Figure 1.4. Orders by city for USA
Figure 1.5. Drag-and-drop analysis
Figure 1.6. State-level orders
Figure 1.7. Customer-level orders
Figure 1.8. Filtered data
Figure 1.9. Execution of an analytics query
Figure 1.10. Increased performance with Mondrian
Chapter 2. Mondrian: a first look
Figure 2.1. Mondrian running in Pentaho
Figure 2.2. Pentaho login page
Figure 2.3. Pentaho User Console (PUC)
Figure 2.4. A Pentaho report: Product Sales Report
Figure 2.5. CDF: Product Sales by Month
Figure 2.6. Saiku: Product Sales by Year
Figure 2.7. Interactive analysis with Saiku
Figure 2.8. Save a report
Figure 2.9. Results showing comparison to same quarter a year ago
Figure 2.10. Sales schema
Figure 2.11. Getting data to the analyst
Figure 2.12. Normalized data vs. star schemas
Figure 2.13. Loading the data warehouse using ETL
Figure 2.14. Using Kettle for ETL
Chapter 3. Creating the data mart
Figure 3.1. Analytic architecture overview: data is copied (and enriched) from the source systems to a dedicated analytic environment, which is where users (via Mondrian) access analytic data.