Siebel Analytics life cycle
Collect Business Requirements.
Recognize source systems.
Plan ETL to load to a DW if source data doesn’t exist.
Build a repository.
Build dashboard or use answers for reporting.
Define security.
Based on performance, decide an aggregations and/or caching mechanism.
Testing and QA.