TDWI Data Warehousing Concepts and Principles: An Introduction to the Field of DataWarehousing

This initial course is an introductory course and spoke of these subjects at a conceptual level with no "nitty-gritty" detail. It was comprised of four modules, "Data Warehousing Concepts", "Data Warehousing Architecture", "Data Warehouse Implementation", and "Data Warehouse Operation".

In the "Concepts" module (Module 1) we discussed the various definitions of a Data Warehouse from Inmon, Osterfelt, Barquin, Kimball, and the TDWI summary. We discussed the framework of "components" that make up BI and D, ETL and its various targets (Data Mart, Data Warehouse, Staging), and the role of those targets. We finished off the module by going through an overview of the data warehousing process, discussing the differences between BI and IT Projects and BI projects and BI Programs, and going through the deliverables of the program and projects. We took the charter and readiness assessment in detail to lead into Module 2.

In the "Architecture" module (Module 2) we continued our path down the process by discussing Business Architecture, Defined Data Architecture, Technology Architecture, Project Architecture, and Organizational Architecture. In the business architecture we discussed the the business context for the data warehouse (drivers, goals, strategies, tactics, and results), and business metrics and management (BPM, BAM, CRM, SCM). In the defined data architecture we discussed data analysis (scenarios-based, goal-based, process-based), business questions, data modeling concepts, warehousing targets analysis (i.e. fact-qualifier table), and metadata requirements. We also discussed technology, project, and organizational architechure.

In the "Implementation" module (Module 3) we discussed Implementation Planning, Warehouse Data Modeling, Implementing Data Warehouse Architecture, Data Warehouse Process Model, Deployed Technology, Implementation Components, and Delivery Results. Warehouse data modeling covered the differences between relational (normalized) and dimensional data in the logical model as well as defining the role of the logical model. Implementing data warehouse architecture introduced the differences between the Inman and Kimball architectures as well as the role of the data warehouse in each architecture. It also introduced the independent data mart, the staging area, and the ODS. The data warehouse process model covered the ETL process in a bit more depth and reviews metadata. The technology, implementation concepts, and delivery results were brief overviews of the subjects.

In the "Operation" module (Module 4) we briefly discussed Business Services, Managed Quality, and Managed Infrastructure. We discussed Data Warehouse Administration in some detail. The administration subject covered data refresh, managed platforms, managed environment, and customer service.

Takeaways:
Inman versus Kimball architecture (Hub and Spoke versus Bus)
John Sackman Model (Contextual, Conceptual, Logical, Structural, Physical, Implemented)
Data Warehousing Program/Project Process and Deliverables