Project management is the discipline of planning, organizing, securing, and managing resources to achieve specific goals. A proper management of data warehousing project may lead to successful implementation whereas lousy project management can cause the project to fail inspite of best technical resources.
Data warehousing projects are one of its kinds. All data warehousing projects do not pose same challenges and not all of them are complex but they are always different. This article illustrates the top 5 challenges that often plague modern data warehousing developments. Knowing these challenges upfront is your best bet to avoid them.
This paper outlines some of the most important (and equally neglected) things that one must consider before and during the design phase of a data warehouse. In our experience, we have seen data warehouse designers often miss out on these items merely because they thought them to be too trivial to attract their attentions. Guess what, at the end of the day such neglects cost them heavily as they cut short the overall ROI of the data warehouse.
An enterprise data warehouse often fetches records from several disparate systems and store them centrally in an enterprise-wide warehouse. But what is the guarantee that the quality of data will not degrade in the process of centralization?
Testing in data warehouse projects are till date a less explored area. However, if not done properly, this can be a major reason for data warehousing project failures - especially in user acceptance phase. Given here a mind-map that will help a project manager to think all the aspects of testing in data warehousing.
"Project Managers" are inevitable. Love them or hate them, but if you are in a project, you have to accept them. They are Omnipresent in any project. They intervene too much on technical things without much knowledge. They create unrealistic targets and nonsensical methods of achieving them. And they invariably fail to acknowledge the individual hard work. Are they of any use?