9890-Case Study_IBM Cognos FM Cardinality_Dterminant Behaviors

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    10-Apr-2012 IBM Cognos Framework Manager    Case Study: Cardinality & Determinant Behavior Saravanan Vajjiravel COGNOS P r a c t i c e Learn. Adapt. Belive. Succeed with Proven Solutions  COGNOS P r a c t i c e Learn. Adapt. Belive. Succeed with Proven Solutions Contents Case Study: IBM Cognos Framework Manager  –  Cardinality & Determinant Behavior  ................... 3 Introduction  ............................................................................................................................................. 3 Cardinality Types  .................................................................................................................................... 3 Model Advisor Generation  ..................................................................................................................... 5 Sample Data  ............................................................................................................................................ 7 Case Study: Cardinality Behavior  ......................................................................................................... 7 Case 1: ORDER_HDR (1:1) ORDER_DTL (1:N)  ....................................................................... 7 Case 2: ORDER_HDR (1:N) ORDER_DTL (1:1)  ....................................................................... 8 Case 3: ORDER_HDR (1:1) ORDER_DTL (1:1)  ....................................................................... 9 Case Study: Determinant Behavior  .................................................................................................... 10  COGNOS P r a c t i c e Learn. Adapt. Belive. Succeed with Proven Solutions Case Study: IBM Cognos Framework Manager  –   Cardinality & Determinant Behavior Introduction In general, the term Cardinality defines the Relationships exist between two query subjects. The cardinality of a relationship is the number of related rows for each of the two query subjects. The rows are related by the expression of the relationship; this expression usually refers to the primary and foreign keys of the underlying tables. IBM® Cognos® software (includes Framework Manager, Report Studio) uses the cardinality of a relationship in the following ways:    to avoid double-counting fact data    to support loop joins that are common in star schema models    to optimize access to the underlying data source system    to identify query subjects that behave as facts or dimensions  A query that uses multiple facts from different underlying tables is split into separate queries for each underlying fact table. Each single fact query refers to its respective fact table as well as to the dimensional tables related to that fact table.  Another query is used to merge these individual queries into one result set. This latter operation is generally referred to as a stitched query.  You know that you have a stitched query when you see coalesce and a full outer join. Cardinality Types IBM® Cognos® software supports both minimum-maximum cardinality and optional cardinality. In 0:1, 0 is the minimum cardinality, 1 is the maximum cardinality. In 1:n, 1 is the minimum cardinality, n is the maximum cardinality.  A relationship with cardinality specified as 1:1 to 1:n is commonly referred to as 1 to n when focusing on the maximum cardinalities. Therefore a 1 to n relationship can also be specified as:    0:1 to 0:n    0:1 to 1:n    1:1 to 0:n    1:1 to 1:n  COGNOS P r a c t i c e Learn. Adapt. Belive. Succeed with Proven Solutions Use the Relationship impact statement in the Relationship Definition dialog box to help you understand cardinality. For example, ORDER_HDR (1:1) is joined to ORDER_DTL (1:n). It is important to ensure that the cardinality is correctly captured in the model because it determines the detection of fact query subjects and it is used to avoid double-counting factual data. When generating queries, IBM Cognos software follows these basic rules to apply cardinality:    Cardinality is applied in the context of a query.    1 to n cardinality implies fact data on the n side and implies dimension data on the 1 side.     A query subject may behave as a fact query subject or as a dimensional query subject, depending on the relationships that are required to answer a particular query. Use the Model Advisor to see an assessment of the behavior implied by cardinality in your model.
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