~ Seminar Outline
- Definitions and Characteristics
- Problems that lead to data warehouse
- Goals and ojectives of data warehouse
- Data warehouse terminology
- Data Warehouse Architecture
- Technical architecture
- OLTP vs. Data Warehouse
- Operational Data Store vs. Data Warehouse vs. Data Mart
- Characteristic and types of an Operational Data Store
- Characteristic of a Data Warehouse
- Characteristic of a Data Mart
- Audit and security implications
- Audit and Security Control Risks
- Why 60% of DW projects fail
- Challenges to Data Warehousing
- Inherent risks
- Risk mitigatigation
- Data Warehouse Infrastructure
- Hardware
- Software/Tools
- Standards
- Methodology
- Organizational structure
- Data Management
- Is the data clean and integrated?
- Will we get consistent reports?
- Dirty data categories
- Data cleansing issues
- Data transformation audit
- Auditing Data Models And Meta Data
- Where did it come from and where did it go?
- Logical data model (process/access independent)
- Data Warehouse data model (database access)
- Physical data model (DBMS specific)
- Metadata components
- Case tools & repositories
- Why Data Warehouse Methodology Is Different
- RAD (Rapid Application Development)
- Iterative (phased development)
- Spiral (looping activities)
- Tasks & deliverables
- Audit reviews
- Project planning and control challenges
- New Organization
- Culture shift
- Roles & responsibilities
- Training & knowledge transfer
- Contractors/Consultants
- Critical Success Factors
- What a critical success factor is
- Identifying and auditing critical success factors
- Common DW success criteria
- Measuring results
- The Development Contract
- Functional scope
- User expectations
- User responsibilities
- Service Level Agreements
- Components of a Development Contract
- Selecting the first DW iteration (1st project)
- Understanding DW access tools:
- Evaluating products
- Evaluating vendors
- Reference checks
- Getting the most from your vendors
- Traps to be aware of
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