Data Warehouse Project Management, Volume 1
According to Earl Hadden & Associates, 85% of data warehouse (DW) projects fail to meet objectives, while 40% fail completely. Effective project management can reduce the possibility of failure. The average DW takes about 3 years to build, and costs $3-5 million. A project of this magnitude requires a project manager, analogous to the software project manager. Since many of the activities and challenges of data warehousing are new, even experienced project managers need guidance and a means of tapping into best and avoiding worst practices. And while there are many books available on different aspects of data warehousing, none target the project manager the way this book does. This book will contain templates, examples, and checklists that will be extremely useful to the project manager in proposing, staffing, designing, developing, and maintaining a data warehouse.
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able activities analysis application developers benefits budget business units Chapter complete cost Data Administration data architecture data cleansing data element data marts data quality data ware data warehouse database data warehouse environment data warehouse objectives data warehouse project database design decision support deliverables denormalization dirty data document ETL tool evaluation example extract/transform/load functions goals and objectives hardware identify impact implementation integrated interface involved logical data model marketing measure ment metadata Methodology number of users OLAP operational systems percent performance physical data model problems Project Agreement project manager project plan QJ QJ queries and reports query tool RDBMS repository requirements response risks roles schedule scope creep service level agreements skills source data source files specific sponsor star schema success target databases tasks team members technical tion types understand vendors warehousing