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Don Burleson Blog 







Data Transformation Analysis

Oracle Tips by Burleson Consulting

The Data Warehouse Development Life Cycle


When performing data query analysis, it is critical to note how the data will need to be transformed in order to meet the needs of end users. Data transformation analysis involves two specific tasks: data classification and data dissection. Data classification involves taking a data entity and classifying all permutations of the data entity, while data dissection is breaking a single data value into derivative components. Both of these activities are essential for a valid and complete warehouse analysis.

Data classification falls into two categories, single valued classification and multi-valued classification. We may encounter a data entity that has many permutations, and each permutation may have its own unique data values. For example, we may be designing a data warehouse for a vehicle rental organization. A rental vehicle may be a sailboat, a car, or an airplane. While each of these entities will be represented in our warehouse as a vehicle, each entity type has distinct data attributes that do not apply to the other entities. A query that references average hull length would not apply to airplanes and cars. These are called single-valued classifications, in that there are distinct data values that ally to each class of entities. Multi-valued data classification applies to mutually exclusive values between data items. For example, we could track the sex of a customer with a multivalued flag that would be set to M, F, and U.

Note: The U value is for Unknown sex, as in the case with customers with unisex names like Pat, Chris, or Shelby.

To illustrate the importance of class hierarchies in a data warehouse analysis, let’s take a look at how data classification may aid data warehouse queries. To illustrate the principle of data classification, let’s return to the Guttbaum’s example. Recall that customer information is collected at the time a customer obtains a Grocery Club Card, and transaction information is obtained at the time a customer “swipes” the Grocery Club Card at the checkout counter.

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