3. Defining the Project
Three possible scenarios for initiating a DW
project
▪ Demand form a lone business executive, a DW believer
▪ Demand from multiple business executives
▪ No demand from business executives, initiated by a CIO
4. Defining the Project
Assessing the Readiness (of the enterprise) for
a DW
▪ 5 desirable factors
▪ Strong Business Management Sponsor(s)
▪ Compelling Business Motivation
▪ Business Partnership
▪ Existence of Analytic Culture
▪ Technical Feasibility
5. Defining the Project
1. Developing the Preliminary Scope
Scope and justification for the initial delivery
Initial focus: single business requirement supported by data from
few sources (start ‘small’)
Limiting the number of initial DW users
6. Defining the Project
2. Building the Business Justification
• Determining the Financial Investments and Costs
– HW, SW, Development, Maintenance, Education, etc.
• Determining the Financial Returns and Benefits
– Focus on revenue or profit enhancement, rather than
reducing cost
– Describe and quantify the opportunities and benefits that
DW can bring (e.g using a proposed DW can reduce the
cost of acquiring new customers by $75 each, while
adding more new customers annually, than before)
• Combining the Investments and Returns to Calculate ROI
7. Planning the Project
1. Establishing the Project Identity
▪ naming the project
2. Staffing the project
▪ Sponsors and Drivers
▪ Project Managers and Leads
▪ Core Project Team
▪ Business System Analyst, Data Modeler, DW-DBA, Data Staging Designer,
End User Application Developer, DW Educator
▪ Special Teams (contribute on a special, limited basis)
▪ Technical/Security Architect, Tech-Support Specialist, Data Staging
Programmer, Data Steward (temp data administrator), DW QA Analyst
3. Developing the Project Plan
▪ The plan should be integrated and detailed
8. Some best practices for implementing a data
warehouse (Weir, 2002):
Project must fit with corporate strategy and
business objectives
There must be complete buy-in to the project by
executives, managers, and users
It is important to manage user expectations about
the completed project
9. Some best practices for implementing a data
warehouse (Weir, 2002):
The project must be managed by both IT and
business professionals
Develop a business/supplier relationship
Be politically aware
10. Failure factors in data warehouse projects:
Cultural issues being ignored
Unclear business objectives
Unrealistic expectations
11. Issues to consider to build a successful data
warehouse:
Starting with the wrong sponsorship chain
Setting expectations that you cannot meet and
frustrating executives at the moment of truth
Loading the warehouse with information just
because it is available
Choosing a data warehouse manager who is
technology oriented rather than user oriented