Oracle Business Intelligence and Data Warehousing Practice Notes and Knowledge Repository

  • About Me

    Hello Friends,

    This is Santosh Kumar Gidadmani, a Business Intelligence and Data Warehouse Enthusiast passionate about blogging articles in the BI, Data warehousing, space. This is my attempt to share my experience and knowledge on Oracle BI & Data Warehousing Subjects.

  • OBIEE 11g Certified Implementation Specialist

  • Oracle Partner Network Certified Specialist

  • Visit My Profiles

  • Enter your email address to subscribe to this blog and receive notifications of new posts by email.

    Join 73 other followers

  • Blog Hits Since Nov 2010

    • 364,321 Hits
  • Live Traffic

  • Visitors Country

    Since-Mar'12Free counters!

Archive for the ‘DW Aproaches’ Category

Data Warehouse Approaches

Posted by Santosh Kumar Gidadmani on January 9, 2011

There are two major approaches to data warehouse design.

1. Bottom-up approach

• This approach is recommended by Kimball.

• In the bottom-up approach data marts are first created to provide reporting and analytical capabilities for specific business processes.

• Data marts contain, primarily, dimensions and facts. Facts can contain either atomic data and, if necessary, summarized data. The single data mart often models a specific business area such as Sales or Production.

• These data marts can eventually be integrated to create a comprehensive data warehouse.

• The integration of the data marts in the data warehouse is centered on the conformed dimensions.

• The actual integration of two or more data marts is then done by a process known as "Drill across". A drill-across works by grouping (summarizing) the data along the keys of the (shared) conformed dimensions of each fact participating in the "drill across" followed by a join on the keys of these grouped (summarized) facts.

• Some consider it an advantage of the Kimball method, that the data warehouse ends up being "segmented" into a number of logically self contained and consistent data marts, rather than a big and often complex centralized model.

• Business value can be returned as quickly as the first data mart is built.

2. Top-down approach

• This approach is recommended by Bill Inmon.

• Inmon is one of the leading proponents of the top-down approach to data warehouse design, in which the data warehouse is designed using a normalized enterprise data model.

• In the Inmon vision the data warehouse is at the center of the "Corporate Information Factory" (CIF), which provides a logical framework for delivering business intelligence (BI) and business management capabilities.

• The top-down design methodology generates highly consistent dimensional views of data across data marts since all data marts are loaded from the centralized repository.

• Generating new dimensional data marts against the data stored in the data warehouse is a relatively simple task.

• The main disadvantage to the top-down methodology is that it represents a very large project with a very broad scope, cost and time.

• In addition, the top-down methodology can be inflexible and unresponsive to changing departmental needs during the implementation phases.

– Santosh

Posted in Data Warehousing, DW Aproaches | Leave a Comment »

%d bloggers like this: