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Project phased delivery

Oracle Tips by Burleson Consulting

The Data Warehouse Development Life Cycle

The Project Delivery Schedule

Unlike many traditional information system projects where a new system is being developed to replace a legacy system, the data warehouse project does not need to have a firm delivery date. In fact, most successful data warehouse project follow an iterative delivery schedule, where small pieces of the data warehouse are delivered, one at a time, widening in scope, until the completed warehouse is delivered (see Figure 2.5).

Figure 2.5 A phased delivery schedule for a data warehouse.

As you can see in Figure 2.5, small pieces of the data warehouse can be delivered independently from other pieces. In general, the slices of the data warehouse fall into two categories: data slices and function slices. For example, a data warehouse manager may be able to deliver the sales data for 1995 through 1997 to end-user managers within six months, and then, while the end-users use the 1995-97 data, the 1993-94 data can be extracted and loaded into the data warehouse. In addition, functional delivery partitioning is common for the data warehouse. Cross-tabulations of summary data (multidimensional displays) can be delivered quickly so that end-users can use this functionality, while the warehouse team completes the simulation and modeling components of the data warehouse system.

When the overall project delivery schedule is examined, designers often notice many opportunities for concurrent development exist, as shown in Figure 2.6. In this Gantt chart, you can see how the development of the end-user interface can proceed at the same time as the data extraction and cleaning processes are performed. The effective application of human resources to these types of concurrent tasks is called crashing a project, and it has been demonstrated that data warehouse projects have many opportunities to accelerate the delivery times.

Figure 2.6 Gantt chart for a data warehouse project.

This is an excerpt from "High Performance Data Warehousing", copyright 1997.
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