This microsoft project plan encompasses project planning and activation, project control, project activation, business case development, business question assessment, architecture review and design, tool selection, iteration project planning, detail design, implementation, transition to production and ending the project--everything you need to build a data warehouse!. Dimensional nature of business data even though the users cannot fully describe what they want in a data warehouse, they can provide you with very important insights into how they think about the business.2/23/2012 3.planning & project management/d.s.jagli 12. Data warehousing project management planning and organizing the data warehouse project includes: defining scope and objectives avoiding major data warehouse mistakes choosing enterprise data warehouse vs. data mart getting the right sponsor forming the team.
� the effort of data warehouse project has been successful if there is critical effective project management. � project management issues are applied to build success data warehouse projects : o project management principles some of the guiding principles that pertain to data warehouse projects exclusively are as follows: o sponsorship. Management in that a data warehouse is never really a completed project. every phase of a data warehouse project has a start date and an end date, but the data warehouse will never go to an. White paper - data warehouse project management managing the technical architecture the technical architecture of a data warehouse is the framework on which the solution is delivered. data warehouses are often described as �complex� without further explanation..
No comments:
Post a Comment