Sunday, April 23, 2006

7:00 pm - 8:00 pm

Level: Intermediate

Data Modelers, Data Analysts, Application Developers or DBA's often have a tendency when developing a new data store (whether Transactional or Decision Support) to immediately start developing a Physical Data Model. However, for best results Conceptual Data Models should be developed prior to Logical Models, Dimensional Models and Physical Models. Developing a Physical Data Model before Conceptual, Logical and Dimensional (if appropriate) models can lead to less than optimal production systems that add additional complexity, require extensive maintenance and result in poor extensibility. Conceptual Data Modeling is used to identify:

• Business Entities
• Entity Subtypes
• Relationships
• Cardinality
• Optionality

Conceptual Data Modeling is a very effective means for reflecting your understanding of business requirements back to business analysts for validation. Conceptual Data Models also provides effective documentation of business subject areas – knowledge is retained in the models, not just in someone’s head.

Pete Stiglich is a Senior Consultant with Enterprise Warehouse Solutions. Pete has nearly 20 years of IT experience in industries such as Retail, Manufacturing, Telecom, Government and Banking. Pete has extensive experience in Data Warehousing, Business Intelligence, CRM and Customer Data Integration (CDI), particularly in Data Modeling, Architecture, Meta Data, ETL, Data Quality and Database Administration. Pete has developed and taught courses on Dimensional Modeling, SQL, Data Quality and XML. He can be reached at pstiglich@ewsolutions.com.