How are They Different

How are They Different?

Let us take a dose look at Figure 2-5. here are the two different basic approaches: (I) overall data warehouse feeding dependent data marts, and (2) several departmental or local data marts combining into a data warehouse. In die first approach, you extract data from the operational systems; you then transform, clean, integrate, and keep the data in the data warehouse. So, which approach is best in your case, the top-down or the bottom-up approach'? Let us examine these two approaches carefully. 

Figure 2-5 Data wart /muse versus data mart.

Top-Down Various Bottoms-Up Approach
Top-Down Approach

The advantages of this approach are:

• A truly corporate effort, an enterprise view of data
• Inherently architecture --not a union of disparate data marts
• Single, central storage of data about the content
• Centralized rules and control
• May see quick results if imp1emerftd with iterations 

The disadvantages are:

• Takes longer to build even with an iterative method
• High exposure/risk to failure
• Needs high level of cross-functional skills
• High outlay without proof of concept

This is the big-picture approach in which you build the overall, big, enterprise-wide data warehouse. Here you do not have a collection of fragmented islands of information. The data warehouse is large and integrated. This approach, however, would take longer to build and has a high risk of failure. If you do not have experienced professionals on your team. This approach could be dangerous. Also, it will be difficult to sell this approach to senior management and sponsors.