Data Warehouse Architecture

Team-Fly

Building a house is analogous to building a data warehouse. The architect draws up a blueprint based on your needs and requirements. During the design process, the architect makes sure that your living requirements are met, house structures comply with all building codes, and utilities and services are based on industry standards. If the house does not adhere to an architectural plan, its integrity will always be in question.

The key benefit of a well-architected data warehouse is that it will fit right into your current corporate information-supply-chain framework and will adapt to new and changing business intelligence and the OLTP application landscape. An enterprise data warehouse architecture defines basic principles, standards, technologies, methodology, and common services needed to meet diverse data objects needed for business intelligence across the corporation. Examples of such services are a common metadata repository, data replication or transformation standards, data access, and data load APIs. When data marts are designed based on enterprise data warehouse architecture, problems associated with information content inconsistency are eliminated, and information encapsulated in data objects has the same meaning across the enterprise decision support systems-data marts or data warehouse. This architected approach eliminates the data quality problems associated with data puddles.

The SAP Business Information Warehouse (SAP BW) follows this paradigm. Under one framework, you can have a huge extraprise data warehouse or a hierarchy of enterprise data warehouses or data marts, all conforming to the same architecture, infrastructure, and information delivery methods.


Team-Fly


Business Information Warehouse for SAP
Business Information Warehouse for SAP (Prima Techs SAP Book Series)
ISBN: 0761523359
EAN: 2147483647
Year: 1999
Pages: 174
Authors: Naeem Hashmi

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