The Data Warehousing Development Lifecycle
Select the Implementation Strategy
Top Down Approach
Bottom Up Approach
Select the Development Methodology
Structured Analysis & Design (Waterfall) Method
Spiral Development Method
Develop the Business Objectives
What is the target market for the data warehouse?
What are currently used or planned platforms?
What are planned capabilities in terms of features and functions?
What are the various data sources that can and/or must be integrated into the
When should the data warehouse become operational?
Select an Initial Implementation Scope
Typical dimensions for restricting scope:
Number & Types of Department Served
Number of Data Sources Selected
Subset of Enterprise Model Selected
Time Allocated for 1st Project
Dimensions can be broadly divided into two categories:
Scope determined from the perspective of the business user of the
Who are the departments that need to use the data warehouse
initially and for what purpose?
What are the range of business queries that must be initially
answered by the data warehouse?
Scope determination based on technology considerations
What is the size of the data warehouse metamodel?
What is the size of data inside the data warehouse?
What are the input sources of data and how many are they?
How usable is the data from the data sources?
How well are the data sources documented?
What is the level of Integrated Management Facilities?
What is the availability of logical models and CASE tools?Is
there an Enterprise Data Model available?
Can existing skills and human resources be used?Will thedata warehouse be implemented on existing platforms or onplatforms similar to existing ones?
Select an Architectural Approach
Operational storage versus using copies of operational data
Data warehouse only
Data marts only
Data warehouse and data marts
Platform and infrastructure partitioning
Two-tier client/server architecture
Three-tier client/server architecture
Build a Program and Project Plans Budget
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