1 dw projectplanning
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The document discusses planning for a data warehousing project. It recommends defining the project scope by starting small with a single business requirement and limited users. It also recommends assessing organizational readiness, developing a business justification by quantifying costs/investments and potential financial benefits/returns to calculate ROI, establishing the project identity and teams, and creating an integrated project plan. It notes best practices like ensuring executive buy-in and a focus on business objectives. Common failure factors are listed as cultural issues being ignored, unclear objectives, and unrealistic expectations.
1 dw projectplanning
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- 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