Managing Data Warehouse Projects: The Key Issues

by William Shackelford

Dallas, September 8-9, 1997

What's Happening

As your Data Warehouse continues to evolve, managing the project becomes increasingly difficult. Each project team faces the daunting task of planning and estimating activities they have never done before using technology they have never used before. In addition, Data Warehouse clients tend to be diverse and disconnected people from multiple organizations with conflicting priorities. To juggle these unknowns requires the tools and techniques covered in this workshop. Data Warehouses must be created within a mode of discovery - they will always need to evolve. For this reason, rigorous techniques are needed to manage the uncertainty.

About This Seminar

The activities of creating and supporting a Data Warehouse can take on a life of their own if they are not properly managed. The Data Warehouse developer must have the skills and knowledge to properly plan, organize and control the chaos. This workshop will answer the following questions for participants:

· What steps must be taken to efficiently manage a Data Warehouse project?
· How can the risk and constraints of a Data Warehouse project be quantified?
· How do you avoid Data Warehouse iterations turning into death spirals?
· What tools and techniques can be used to track the progress of Data Warehouse work?
· How can the scope of a Data Warehouse project be established?
· How can Data Warehouse projects be accurately estimated and planned?

What Makes This Seminar Unique

This seminar provides participants with practice in project management techniques that they can apply to their own Data Warehouse projects. Through case studies and team interaction, students will leave with the ability to tighten up the management of their own Data Warehouse projects and the techniques to minimize the risk of Data Warehouse project failure.

Who Should Attend &
What You Will Learn

IS developers responsible for the analysis, design, development, implementation and administration of Data Warehouses will learn…

• How to avoid the common risks inherent to Data Warehouse projects
• How to successfully complete your first Data Warehouse project after hearing the success and failure stories of other companies
• A strategy for delivering the most business benefit in the smallest amount of time

IS Development Managers responsible for Data Warehouses will learn…

• The critical success factors that make or break Data Warehouse projects
• How to accurately estimate the people and time needed to deliver a successful Data Warehouse

IS Data Warehouse customers will learn…

• The role you must play in determining how the Data Warehouse will help the business
• How to accurately estimate your own involvement in Data Warehouse implementation
• Realistic expectations about what Data Warehouse can and cannot deliver

Seminar Outline

1. Why Data Warehouse?

   1. Problems that lend to Data Warehouse

   2. The goals of a Data Warehouse

   3. On-line transaction processing (OLTP) vs. Data Warehouse

   4. How a Data Warehouse is used

   5. Definitions

   6. Other terms

   7. Implementing a Data Warehouse

2. Create a Project Definition

   1. Dare to properly manage resources

   2. Risk assessment

      1. Common risks: creeping scope

      2. Common risks: unrealistic expectations

      3. Quick n’ Dirty risk assessment

   3. Scenario planning

   4. Data Warehouse failure

   5. Common risks: changing priorities

   6. Challenges to Data Warehouse quality

      1. Organizational issues

      2. Cultural imperatives

3. Iterative Data Warehouse Development

   1. The importance of iteration

      1. "Big Bang" vs. Iteration

   2. What is RAD?

   3. Business events

   4. Starting from a relationship matrix

      1. Top down data modeling: The Chocolate Factory

      2. The Chocolate Factory: relationship matrix

      3. The Chocolate Factory: The Entity Relationship Model

   5. Is it a data entity?

   6. Progression of detail

   7. Adding optionality

   8. Refinement

   9. Metadata

   10. Different views of data

   11. Identifying the source

   12. Types of data

   13. Logical and physical synchronization

   14. Time series data

   15. Drilling down

   16. Data replication

   17. Prototyping

   18. Roles and responsibilities

   19. Data Warehouse challenges

   20. What’s different?

   21. Data Warehouse failures

   22. Data Warehouse roles

       1. End user (client)

       2. User liaison

       3. End user support

       4. Data administration

       5. Data analyst

       6. Application developer

       7. Security office

       8. Database administration

       9. Technical services

       10. Strategic architecture

       11. Data Warehouse project manager

       12. Technical advisory board

       13. Business advisory board

4. Create a Project Plan

   1. Planning for Data Warehouse

   2. Data Warehouse complexity

   3. Enterprise Network Computing Architecture (ENCA)

   4. The Data Warehouse project plan

   5. Project management techniques

   6. Creating a work breakdown

   7. Building a schedule

   8. A RAD approach

   9. MapXpert for Data Warehouse

      1. Phase 1 - Project definition & planning

      2. Phase 2 - Establish the DW technology platform

      3. Phase 3 - Database & migration development

      4. Phase 4 - Query/Reporting development

      5. Phase 5 - Implementation

      6. Phase 6 - Post implementation review

   10. Estimating

   11. Project related

   12. Environmental

   13. Duration adjustments

   14. Core technologies needed

   15. Questions to be answered

   16. Product categories

   17. Criteria for evaluation

   18. Selecting desktop tools

   19. Higher level analysis

   20. Metadata strategy

   21. Money

   22. Who should evaluate

   23. Selling and communicating

   24. Traps

   25. Seven deadly sins

   26. Assessing readiness

5. Managing the Project

   1. What to do if you’re behind

   2. Tips for success

   3. Designing a Data Warehouse for the future

   4. Knowledge transfer

6. Reviewing the Project

   1. Post project review

   2. Final points to remember

   Exercises

About Your Instructor

William Shackelford is a Senior Learning Facilitator for Russell Martin & Associates, a firm specializing in timely technology challenges such as Data Warehouse, Year 2000 and Project Management. He has also been President of Shackelford and Associates since 1982. He completed his undergraduate and graduate studies at Indiana University, Universitat Hamburg, Illinois Institute of Technology and the University of Illinois in music, accounting, business administration and computer science. His extensive background in business systems development involving systems analysis, design, testing and support experience has brought success to his customers including Amoco, Kemper, R.R. Donnelley, Avon and Dean Witter.

Meeting Site and Hotel Information

Dallas, September 8-9, 1997
Doubletree Hotel at Campbell Centre
(214)691-8700

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Managing Data Warehouse Projects: The Key Issue

$995

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