Ten Mistakes to Avoid Web Archive

Below you will find an archive for the <I>Ten Mistakes to Avoid</I> series. The archive includes booklets dating back to 2001 when TDWI launched its new Web site and began publishing Member benefit publications online.

• 05/17/02

Ten Mistakes to Avoid When Constructing a Real-Time Data Warehouse Q3 2003

Ten Mistakes to Avoid for Mature Data Warehouses

• Foreword
• Mistake 1: Active Participation by Key Business Experts
• Mistake 2: Failure to Promote the Data Warehousing Program
• Mistake 3: No Calculation of the Data Warehousing Program's ROI
• Mistake 4: Lack of a Data Quality Program
• Mistake 5: Not Having Encompassing Architecture with a High Degree of Sharing
• Mistake 6: No Ongoing, Proactive Management of Performance and Capacity Planning
• Mistake 7: Lack of Appropriate User Data Access Tools
• Mistake 8: No Data Warehouse Team Ownership of a 'Center of Excellence'
• Mistake 9: Failure to Incorporate Third-Party External Data into the Warehouse
• Mistake 10: An Inflexible Data Loading Architecture that Inhibits Real-Time Loading
• About the Author: William McKnight

Ten Mistakes to Avoid for Data Warehousing Acquisition Architects

• Foreword
• Mistake 1: Designing for the Present, Not the Future
• Mistake 2: Failing to Exploit Changed Data
• Mistake 3: Skipping Steps Needed to Understand Source Systems
• Mistake 4: Underestimating the Time Needed for Acquisition Design and Implementation
• Mistake 5: Selecting Data from “Easy” Sources Instead of the “Right” Sources
• Mistake 6: Miscalculating the Cost of Poor Data Quality
• Mistake 7: Failing to Invest in Meta Data
• Mistake 8: Failing to Adjust the Testing Cycle for Data Warehousing Differences
• Mistake 9: 9.Misunderstanding the Differences Between “One-Time” Data Loads and “Ongoing” Loads
• Mistake 10: Inappropriately Using Technology
• About the Author: Karolyn Duncan

Ten Mistakes to Avoid When Planning Your CRM Program

• Foreword
• Mistake 1: Failure to Factor in Strategy
• Mistake 2: Letting Vendors, Not Requirements, Drive the Need
• Mistake 3: Bypassing Success Metrics
• Mistake 4: Underestimating Data Integration Issues
• Mistake 5: Underestimating System Integration Issues
• Mistake 6: Ignoring Business Processes
• Mistake 7: Underestimating or Overestimating Organizational Change
• Mistake 8: Deferring Discussions of Privacy
• Mistake 9: Assume all CRM Users are LAN Connected
• Mistake 10: Not Closing the Loop Back to Development
• About the Author: Jill Dyché

Ten Mistakes to Avoid When Building an Operational Data Store

• Foreword
• Mistake 1: Missing Scope Document, Including A Mission Statement
• Mistake 2: Missing Development Methodology
• Mistake 3: Misunderstanding Data Currency Requirements Resulting In A Multidimensional Design
• Mistake 4: Using The ODS As A Staging Area For The Data Warehouse
• Mistake 5: Setting Unrealistic Expectations For Update Cycles
• Mistake 6: Not Using The Right Tools
• Mistake 7: Maintaining Significant History In The ODS
• Mistake 8: Poorly Designed Referential Integrity
• Mistake 9: Poor Performance For Reporting
• Mistake 10: Not Creating A Service Management Function And A Program Management Office
• About the Author: Joyce Norris-Montanari

Ten Mistakes Home

Ten Mistakes to Avoid When Constructing a High Performance Data Warehouse

• Foreword
• Mistake 1: Lack of A Meaningful Service
  Level Agreement
• Mistake 2: Treating all Workloads with Equal Priority
• Mistake 3: Reliance on Human Intervention for
  Query Optimization
• Mistake 4: Serial ETL Processing
• Mistake 5: Reloading the Data Warehouse From Scratch on Each Refresh
• Mistake 6: Over Reliance on Summary Tables to Reduce Query Response Times
• Mistake 7: Treating Scalability as One Dimensional
• Mistake 8: Configuring Storage for Capacity Rather Than Performance
• Mistake 9: Omitting Performance Testing in the Deployment Plan
• Mistake 10: Using Design Techniques More Appropriate for OLTP Solutions
• About the Author: Stephen Brobst
• References

Ten Mistakes to Avoid When Modeling Data Warehouses

• Foreword
• Mistake 1: Not gathering business requirements
• Mistake 2: Saving time by not creating a subject area model
• Mistake 3: Delivering normalized tables to drive out mart design
• Mistake 4: Designing the data staging process for the ease of the developers at the expense of the end users
• Mistake 5: Denormalizing without starting with a fully normalized data model
• Mistake 6: Allowing users to drive the level of detail
• Mistake 7: Not having a multi-tiered warehousing environment
• Mistake 8: Developing a data model from a list of required data elements
• Mistake 9: Thinking that you must choose between relational and dimensional models
• Mistake 10: Jumping straight into data mart design
• About the Authors: Karolyn Duncan, Steve Hoberman, and Laura Reeves

Ten Mistakes to Avoid When Building a Data Warehouse Team

• Foreword
• Mistake 1: Hiring yourself
• Mistake 2: Squelching disagreement
• Mistake 3: Confusing titles with roles and responsibilities
• Mistake 4: Talking the walk
• Mistake 5: Thinking one size fits all
• Mistake 6: Pointing fingers
• Mistake 7: Interviewing only for technical skills
• Mistake 8: Limiting Leadership
• Mistake 9: Becoming too task focused
• Mistake 10: All decisions are created equal
• About the Authors: Maureen Clarry and Kelly Gilmore

Ten Mistakes to Avoid When Managing Data Warehouse Projects

• Foreword
• Mistake 1: Accept an unrealistic schedule
• Mistake 2: Take on a failing project
• Mistake 3: Launch a project with a dysfunctional team
• Mistake 4: Choose the wrong sponsor
• Mistake 5: Accepting unrealistic expectations
• Mistake 6: Expand the project scope
• Mistake 7: Skip the project plan
• Mistake 8: Fail to put the project agreement in writing
• Mistake 9: Letting IT drive the project
• Mistake 10: Give others authority to select software
• BONUS Mistake!: Marketing the project yourself

Ten Mistakes to Avoid for Data Warehousing Sponsors

• Foreword
• Mistake 1: Fail to establish a business/IT partnership
• Mistake 2: Fail to ensure continuity in key staffing positions
• Mistake 3: Fail to make provisions for training
• Mistake 4: Overfund or underfund the data warehousing program
• Mistake 5: Postpone implementing a sound data warehousing infrastructure
• Mistake 6: Believe 'technology will solve everything'
• Mistake 7: Take consultants' recommendations without question
• Mistake 8: Fail to plan for the big picture
• Mistake 9: Assume that performance issues can be solved by IT alone
• Mistake 10: Fail to measure success and promote the data warehouse

Ten Mistakes to Avoid for Data Warehousing Managers

• Foreword
• Mistake 1: Not differentiating between program and project management
• Mistake 2: Underestimating the difficulty of acquiring source data
• Mistake 3: Having unrealistic expectations about data quality
• Mistake 4: Strict adherence to either a 'top down' or a 'bottom up' development approach
• Mistake 5: Lack of a meta data plan
• Mistake 6: Lack of detailed historical data
• Mistake 7: Insufficient attention to management and operational issues
• Mistake 8: Excessive use of outsourcing
• Mistake 9: Implementing a non-scalable data warehousing architecture
• Mistake 10: Narrowing the range of solutions before you know the problem

Comments