Prerequisite:   This course assumes basic understanding of project management and data warehousing.

 

Two-Day Course

You Will Learn

• How to recognize and mitigate common DW risks and identify critical success factors
• How to build your BI applications using software releases (based on XP principles)
• How to use a spiral DW methodology to define, plan, and control your project
• How to organize and empower your project teams, including their roles and responsibilities
• How to overcome organizational and cultural barriers to implementing this new approach
• How to coordinate and manage multiple interdependent DW projects under one BI program

Geared To

• Project managers, project leads, business managers, end users

As you are managing your DW project, you draw upon your past experience as a project manager. But to your dismay, you find that in spite of your experience, your DW project is unusually difficult to manage. The requirements appear to be a "moving target." Communication between staff members takes too long. Assigning tasks in a traditional way seems to result in too much rework. Using a traditional methodology does not work. To top it all off, the business users are pressuring you for quick deliverables (90 days or less) as they are still “refining” their requirements. As the DW team scrambles to meet those expectations, data standardization is skipped, testing is cut short, documentation is not done, and quality is compromised. The end result is often an independent data mart – always accompanied by the promise to clean it up later and to consolidate it with the other silo data marts (and data warehouses), which regrettably rarely happens. Sound familiar? So, how can you “have your cake and eat it too?" In other words, how can you do it right and still deliver in 90 days? You have to set aside some of the traditional project management disciplines and try a new approach. In this course, you will learn about self-organizing project teams, spiral methodologies, and “extreme scoping” (a development method based on software releases).

Course Outline

Why traditional project management (PM) does not work on DW projects

• From chaos to architecture
• DW role in BI
• DW goals and objectives
• Traditional development method
• Waterfall methodologies
• Industrial-age mental model
• The time trap
• Proliferation of redundancy
• What’s different about DW projects

Common DW failures and PM challenges

• DW failures
• PM challenges
• The lesson
• Information-age mental model
• Cross-organizational development method

Spiral DW methodology

• Engineering stages
• Business case assessment
• Enterprise infrastructure evaluation (technical and non-technical)
• Project planning
• Requirements definition
• Data analysis
• Application prototyping
• Meta data repository analysis
• Database design
• ETL design
• Meta data repository design
• ETL development
• Application development
• Data mining
• Meta data repository development
• Implementation
• Release evaluation
• Parallel development activities

Software release concept

• Software release guidelines
• Self-organizing project team
• Core team
• Extended team
• Roles and responsibilities

Different project planning process

• Estimate effort for entire application
• Break into software releases
• Create milestones for first release
• Organize parallel development tracks
• Create detailed work assignments
• Create Gantt chart
• Case study (example)

BI portfolio management

• BI steering committee
• BI program management
• BI maturity model

Best practices/critical success factors

• Mitigating DW failures
• Addressing PM challenges

Organizational culture change

• Organizational impact
• Culture shift
• Power shift
• Charge-back policy
• Incentive policy
• New leadership