Building the Data WarehouseEverything you need to know to design, develop, and build your data warehouse The data warehouse solves the problem of getting information out of legacy systems quickly and efficiently. If designed and built right, data warehouses can provide significant freedom of access to data, thereby delivering enormous benefits to any organization. In this unique handbook, W. H. Inmon, "the father of the data warehouse," provides detailed discussion and analysis of all major issues related to the design and construction of the data ware-house, including granularity of data, partitioning data, metadata, lack of creditability of decision support systems (DSS) data, the system of record, migration, and more. This Second Edition of Building the Data Warehouse is revised and expanded to include new techniques and applications of data warehouse technology and update existing topics to reflect the latest thinking. It includes a useful review checklist to help evaluate the effectiveness of the design and explains * How to design and build a data warehouse-including step-by-step guidelines * Migration to the data warehouse from existing architectures * Techniques for using the data warehouse to provide companies with a powerful competitive edge * How to monitor the data warehouse * The role of the data warehouse in reengineering * How to get the most from both star joins and data models * How data marts and OLAP fit with data warehousing techniques * And much more Find out what a data warehouse can do for your company and how to build one tailored to your organization's needs in Building the Data Warehouse, Second Edition. |
Contents
The Data Warehouse Environment | 33 |
The Data Warehouse and Design | 73 |
Granularity in the Data Warehouse | 145 |
Copyright | |
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Common terms and phrases
access of data amount of data analysis application architected environment architecture common created DASD data architect data ware data warehouse data data warehouse development data warehouse environment datamart deliverable departmental derived data detailed data development group distributed data warehouse DSS analyst DSS data DSS environment DSS processing dual levels end user existing systems environment external data extract foreign key functional decomposition global data warehouse identified integration issue iterative legacy level of data level of detail levels of granularity lightly summarized local data warehouse ment metadata methodology multidimensional DBMS NORMALLY EXECUTED ONCE OLAP ONCE OR MULTIPLE operational data operational data store operational environment operational processing operational systems PARAMETERS OF SUCCESS partitioning PRECEDING ACTIVITY profile record pseudocode referential integrity relationship shown in Figure snapshot storage summary data system of record tables Tech Topic tion units of data unstructured data update volume of data