Building the Data Warehouse

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TIME ESTIMATE: Varies widely, depending on the status and quality of the data model.


At the outset, a data model needs to have been defined. The data model needs to have done the following:

■■ Identified the major subject areas

■■ Clearly defined boundaries of the model

■■ Separated primitive from derived data

The following need to be identified for each subject area:

■■ Keys ■■ Attributes

■    Groupings of attributes

■    Relationships among groupings of attributes ■■ Multiply occurring data

■    “Type of” data

The output from this step is a confirmation that the organization has built a solid data model. If the model does not meet the criteria specified, then progress should be halted until the model is brought up to standards of quality.

PARAMETERS OF SUCCESS: The data model will have the following:

■    Major subjects identified

■    Each major subject with its own separate definition of data, including:

■    Subtypes of data

■    Attributes of data

■    Clearly defined relationships of data

■    Defined groupings of data

■    Defined keys

In addition, each group of data that will go into the data warehouse will have DSS data and operational-only data delineated. All DSS data will have its own time-variant key specified, usually as the lower order of a higher key.

DSS2—Breadbox Analysis

PRECEDING ACTIVITY: Data model analysis.

TIME ESTIMATE: From one day to two weeks, depending on how well the scope has been defined, how well the data model has been defined, etc.

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