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Dimensions → Materialized Views\" Dimensions A dimension is a schema object that defines hierarchical relationships … require any space in the database. A typical dimension is city, state (or province), region, and country. See Also: Chapter 11, \"Dimensions\"
Viewing Dimensions → Dimensions can be viewed through one of two methods: Using Oracle Enterprise Manager Using the DESCRIBE_DIMENSION Procedure
Using the DESCRIBE_DIMENSION Procedure → To view the definition of a dimension, use the DESCRIBE_DIMENSION procedure in the DBMS_DIMENSION package. For example, if a dimension is created in the sh sample schema with the following statements: CREATE DIMENSION channels_dim LEVEL channel IS (channels.channel_id) LEVEL channel_class IS (channels.channel_class) HIERARCHY channel_rollup ( channel CHILD OF channel_class) ATTRIBUTE channel DETERMINES
Altering Dimensions → COMPILE; Dimensions can also be modified or deleted using Oracle Enterprise Manager.
Using Oracle Enterprise Manager → All of the dimensions that exist in the data warehouse can be viewed using Oracle Enterprise … Manager. Select the Dimension object from within the Schema icon to display all of the dimensions. Select
Deleting Dimensions → A dimension is removed using the DROP DIMENSION statement. For example, you could issue the following statement: DROP DIMENSION times_dim;
What are Dimensions? → questions. Commonly used dimensions are customers, products, and time. For example, each sales channel of … the retailer's data warehouse system has two important components: dimensions and facts. The … dimensions are products, customers, promotions, channels, and time. One approach for identifying your … dimensions
Multiple Hierarchies → A single dimension definition can contain multiple hierarchies. Suppose our retailer wants to track the sales of certain items over time. The first step is to define the time dimension over which sales will be tracked. Figure 11-2 illustrates a dimension times_dim with two time hierarchies. Figure 11-2 times_dim Dimension with Two Time Hierarchies Description of \"Figure 11-2 times_dim Dimension with
Using Dimensions with Constraints → Constraints play an important role with dimensions. Full referential integrity is sometimes enabled
Creating Dimensions → dimensions, determine whether the child-side columns uniquely determine the parent-side (or attribute … the same table. However, this is not a prerequisite for creating dimensions. \"Using Normalized … OF subcategory CHILD OF category) In addition to the 1:n hierarchical relationships, dimensions also … dimensions
Dropping and Creating Attributes with Columns → You can use the attribute clause in a CREATE DIMENSION statement to specify one or multiple columns that are uniquely determined by a hierarchy level. If you use the extended_attribute_clause to create multiple columns determined by a hierarchy level, you can drop one attribute column without dropping them all. Alternatively, you can specify an attribute name for each attribute clause CREATE or ALTER
Using Normalized Dimension Tables → The tables used to define a dimension may be normalized or denormalized and the individual hierarchies can be normalized or denormalized. If the levels of a hierarchy come from the same table, it is called a fully denormalized hierarchy. For example, cal_rollup in the times_dim dimension is a denormalized hierarchy. If levels of a hierarchy come from different tables, such a hierarchy is either a
Validating Dimensions → relationships described by the dimensions are incorrect, incorrect results could occur. Therefore
11 Dimensions → This chapter discusses using dimensions in a data warehouse: It contains the following topics: What … are Dimensions? Creating Dimensions Viewing Dimensions Using Dimensions with Constraints Validating Dimensions Altering Dimensions Deleting Dimensions
dimensions → A list of one or more dimensions or composites, separated by spaces. When you list multiple … dimensions, all the dimensions must be in the same workspace. LISTBY returns a list of objects that are … dimensioned by all the dimensions you specify. When you specify an unnamed composite, use the following … format:
Dimensions → Sales measure has four dimensions: Time, Customer, Product, and Channel. A particular Sales value
Query Rewrite Using Dimensions → the query using aggregates in the materialized view. Query Rewrite Using Dimensions This section … discusses the following aspects of using dimensions in a rewrite environment: Benefits of Using Dimensions How to Define Dimensions
Overview of Dimensions → A typical data warehouse has two important components: dimensions and facts. A dimension is any
Analyzing Across Multiple Dimensions → enterprise from all necessary combinations of dimensions. We use the term dimension to mean any … category used in specifying questions. Among the most commonly specified dimensions are time, geography … , product, department, and distribution channel, but the potential dimensions are as endless as the … for automotive products,
Query Rewrite Considerations: Dimensions → denormalized dimension tables using the HIERARCHY and DETERMINES clauses of a dimension. Dimensions can … QUERY_REWRITE_INTEGRITY to TRUSTED or STALE_TOLERATED for query rewrite to take advantage of the relationships declared in dimensions.