-
Marketplace
-
Channel Resources
Articles from this Site
Technologies to Take Your Enterprise-Wide BI and DW Program to the Next Level
Data Integration Will Break Out of the Silo: BI and DW Trends, 8 for '08
U.S. Airforce Selects Teksouth
The Song Remains the Same - Data Shadows Systems Continue to be Pervasive for Reporting and Analytics: BI and DW Trends, 8 for '08
Data Warehousing Meets Data Archiving in Information Lifecycle Management
White Papers
Databasing in the 90s: Data and What We're Doing with It!
Spend Data Warehouse on Steroids
Debugging PL/SQL with AgileInfoSoftware OraDebug
Tune Oracle SQL Performance with AgileInfoSoftware
Data Warehouses: What are they and how will they benefit your organization?
Books
What are the successful processes that are followed in the industry for task estimation of a data warehousing project ?
| Q: | I am doing a research on the best and appropriate task estimation process for a data warehousing project and implement the same within the team. I would like to know how others proceed with it? What are the successful processes that are followed in the industry? |
| A: |
Danette McGilvray's Answer: The goal of the task estimation process is to determine the tasks needed to complete the project, estimate effort, and create a draft schedule for completion. Note: The task list is also known as a project plan, a work breakdown structure, or a workplan. When developing the initial task list and timeline with a project team, it is helpful to use a facilitator. The facilitator expedites the process so the project manager and team members are free to focus on determining the actual tasks and effort needed. Depending on the size and scope of the project, you may have more than one project team creating their own project plan for their specific deliverables. The overall project manager then brings together the plans into a master plan. The approach below works whether you have one team or several teams. I will briefly explain a process I have used successfully for many projects. Determine the general approach, high-level phases, and the methodology to be used in the project.
Gather the project team. Manual technique:
|
Danette McGilvray is president and principal of Granite Falls Consulting, Inc., a firm specializing in information quality management to support key business processes around customer satisfaction, decision support and operational excellence. Projects include enterprise data integration programs, data warehousing strategies and best practices for large-scale ERP data migrations for Fortune 50 organizations. For more than ten years she led information quality initiatives at Hewlett-Packard and Agilent Technologies. An accomplished program manager and facilitator, she is an internationally respected expert on data profiling, metrics, quality, audits, benchmarking, and tool acquisition and implementation. McGilvray is an invited speaker at conferences throughout the U.S. and Europe, where she trains other industry experts in enterprise information management and data stewardship. You can reach her at danette@gfalls.com.
For more information on related topics, visit the following channels:


