The Data warehouse Bus Structure: The Bottom-Up Approach

Ralph Kimball designed the data warehouse with the data marts connected to it with a bus Structure.

The bus structure contained all the common elements that are used by data marts such as conformed dimensions, measures etc defined for the enterprise as a whole. He felt that by using these conformed elements, users can query all data marts together. This architecture makes the data warehouse more of a virtual reality than a physical reality. All data marts could be located in one server or could be located on different servers across the enterprise while the data warehouse would be a virtual entity being nothing more than a sum total of all the data marts.

In this context even the cubes constructed by using OLAP tools could be considered as data marts. In both cases the shared dimensions can be used for the conformed dimensions.
This model strikes a good balance between centralized and localized flexibility. Data marts can be delivered more quickly and shared data structures along the bus eliminate the repeated effort expended when building multiple data marts in a non-architected structure. The conformed dimensions along the bus fit very well with the shared dimension and virtual cube capabilities of Microsoft’s OLAP services.

The bottom-up approach reverses the positions of the Data warehouse and the Data marts. Data marts are directly loaded with the data from the operational systems through the staging area. The ODS may or may not exist depending on the business requirements. However, this approach increases the complexity of process coordination. The standard procedure where data marts are refreshed from the ODS and not from the operational databases ensures data consolidation and hence it is generally recommended approach

The data flow in the bottom up approach starts with extraction of data from operational databases into the staging area where it is processed and consolidated and then loaded into the ODS. The data in the ODS is appended to or replaced by the fresh data being loaded. After the ODS is refreshed the current data is once again extracted into the staging area and processed to fit into the Data mart structure. The data from the Data Mart, then is extracted to the staging area aggregated, summarized and so on and loaded into the Data Warehouse and made available to the end user for analysis.

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