The Data Warehouse Toolkit: Practical Techniques for Building Dimensional Data Warehouses, Volume 1
". . . one of the definitive books of our industry. If you take the time to read only one professional book, make it this book." -W. H. Inmon
One of the most dramatic new developments in database design, the dimensional data warehouse is a powerful database model that.significantly enhances managers' ability to quickly analyze large, multidimensional data sets. Written by the leading proponent of this revolutionary new approach, this valuable book/CD toolkit outfits you with all the nuts-and-bolts information you need to design, build, manage, and use dimensional data warehouses for virtually any type of business application, as well as software for querying dimensional data warehouses.
Employing many real-life case studies of data warehouses, Ralph Kimball provides clear-cut guidelines on how to model data and design data warehouses to support advanced multidimensional decision support systems. Beginning with the relatively simple example of a data warehouse for a grocery store, he progresses, step-by-step, through an increasingly complex array of business applications in retail, manufacturing, banking, insurance, subscriptions, and airline reservations. By the end of the book, you will have mastered the full range of powerful techniques for creating, controlling, and navigating dimensional business databases that are easy to understand and navigate.
On the CD-ROM you'll find:
* Software for querying dimensional data warehouses.
* Working models of all the databases described in the book.
86 pages matching Ralph Kimball in this book
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THE GROCERY STORE
THE Mosr POWERFUL DATABASE
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A.C. Nielsen aggregate fact aggregate navigator answer set application Base fact table base-level brand break rows browse queries bytes Chapter column comparison constraint coverage covered item customer dimension data quality assurance data ware data warehouse team DBMS deﬁned deﬁnition design principle dimension keys dimension record dimensional data warehouse dimensional database drilling end user example fact ﬁelds Fact Table Additive ﬁle ﬁnal ﬁnd ﬁrst foreign keys Framis grain grocery store hierarchy identiﬁed interviews inventory invoice join queries legacy system line item mension minidimensions month monthly snapshot Number of base Number of key ODBC OLAP OLTP percent product dimension table product key production data proﬁt query tool relational database row headers schema separate shipments signiﬁcant slowly changing dimensions speciﬁc Star Tracker Table Additive Field track transaction userís value chain vendors Widget