A Data Model solution to analyzing patterns of interest found in transactional data (Master - Detail format). Rules/Pattern Discovery of type IF-THEN rules can be via any ML function (Association Rules, Decision Trees, Domain/Business knowledge etc.). Custom data model enables Pattern Analysis in many new and interesting ways. a) Comparing Historical Performance with Near Real Time Analytics w/o model build activity b) New Product performance w/o model build c) Allow on-demand Deepdives and/or Speedup Deepdives for specific patterns by pre-calculating Pattern-Trx-KPIs via ETL process (optional) d) What If actions on patterns - add, exchange, replace, delete, rotate, etc. e) SQL approach allows us to examine edge cases/anamolies/infrequent fraud cases etc which may not meet the criteria for significance (few cases). f) Find similar - Fraud Trx, Persons of interest (!), complete/partial matching etc. g) Compare patterns/KPIs
