Data Warehouse Configurations For Your Data Warehousing System

A data warehouse configuration is commonly known as the logical architecture. It is the foundation on which a data warehouse is built or you can say the logical architecture is a configuration map of the data to be stored in the warehouse. A Data Warehouse configuration includes a central Enterprise Data Store; an optional Operational Data Store; one or more optional individual business area Data Marts; and one or more Metadata Store or Repositories. When discussing options with your data warehousing consultant, these are some of the things that you must consider.

– Enterprise Data Store (EDS): This is the central repository that supplies atomic integrated information to the whole organization. The EDS can be defined as the cornerstone of a data warehouse and this can be accessed for immediate informational needs as well as for analytical processing to assist strategic decision-making in an organization. The EDS may contain data from the existing subject area operational systems as well as from external sources. This data further feeds individual Data Marts that are accessed by end-user query tools at the user’s desktop. The EDS can also be called as the collection of daily “snapshots” of enterprise-wide data taken over an extended time period. Thus it creates an optimum environment for strategic analysis.

– Operational Data Store: It is a “snapshot” of a moment in time’s enterprise-wide data. An ODS is a set of relational databases designed to perform simple queries on small amounts of data as opposed to the complex queries on much greater volumes of data typically stored in the data warehouse. In other words, an ODS stores only very recent information, rather than storing permanent information like the data warehouse.

– Individual Data Mart: It is the summarized subset of the enterprise’s data specific to a functional area or department, geographical region, or time period. Access to the EDS can often be difficult or slow, thanks to the volume of data it contains. This is when the role of Data Marts comes into play. Data Marts filter, condense and summarize information for specific business areas. However in the absence of the Data Mart layer, users can access the EDS directly.

– Metadata Store or Repository: This is a catalog of reference information about the primary data. It provides users and developers with a road map to the information in the data warehouse. Metadata is further divided into two categories- information for technical use or transformational and information for business end-users. Transformational metadata serves a technical purpose for development and maintenance of the warehouse, while end-user metadata serves a business purpose. Basically, this type of metadata translates a cryptic name code that represents a data element into a meaningful description so that end-users can recognize and use the data. On the other hand, transformational metadata maps the data element from its source system to the data warehouse, identifying it by source field name, destination field code, transformation routine, business rules for usage and derivation, format, key, size, index and other relevant transformational and structural information.

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