- Business Sponsorship: Is there appropriate executive sponsorship, i.e., an identified and engaged steering committee and commensurate funding? DW/BI projects require strong executive sponsorship.
- Business Goals and Scope: Is there a clearly identified business need, purpose, and scope for the effort?
- Business Resources: Is there a commitment by business management to the availability and engagement of the appropriate business subject matter experts? The lack of commitment is a common point of failure and a good enough reason to halt a DW/BI project until commitment is confirmed.
- Business Readiness: Is the business partner prepared for a long term incremental delivery? Have they committed themselves to establishing centers of excellence to sustain the product in future releases? How broad is the average knowledge or skill gap within the target community and can that be crossed within a single increment?
- Vision Alignment: How well does the IT Strategy support the Business Vision? It is vital to ensure that desired functional requirements correspond to business capabilities that are or can be sustained in the immediate IT roadmap. Any significant departures or material gaps in capability alignment can stall or stop a DW/BI program.
A Few Critically Important Architectural Sub-Components, along with their Supporting Activities:
- Conceptual Data Model: What information is core to the organization? What are the key business concepts and how are they related to each other?
- Data Quality Feedback Loop: How are data issues identified and remediated? How are owners of the systems in which issues originate informed about problems and held accountable for fixing them? What is the remediation process for issues that are caused by the DW data integration processes?
- End-to-end Metadata: How does the architecture support the integrated end-to-end flow of Metadata? In particular, is access to meaning and context designed into the architecture? How do data consumers answer basic questions like “What does this report mean?” or “What does this metric mean?”
- End-to-End Verifiable Data Lineage: Are the items exposed to business users traceable to the source systems in an automated, maintained manner? Is a system of record identified for all data?
