Metadata Modeling Guidelines

Metadata modeling
The purpose of metadata modeling is to present a user-friendly representation of the data that is available to your query audience while adding business value where required.
Import and verify metadata
After identifying the metadata that can be used in your model, import only the required items to keep your model manageable. Also, verify the Usage and Aggregate properties on columns.
Remove ambiguity
Ambiguity in model design refers to potential misinterpretations of relationships and their cardinality by the Cognos® Analytics query service.
Model design and presentation
You should always strive to present the metadata to users in a clear and concise manner, logically grouped, and easy to read and understand.
Multi-fact, multi-grain queries
Multiple-fact, multiple-grain queries occur when a table containing dimensional data is joined to multiple fact tables on different key columns.
Enhance the model with additional features
As a modeler, you can use various techniques and features to enhance the model.
Optimizing query performance
Cognos Analytics is designed to take full advantage of your data infrastructure. The primary data access strategy is to delegate data processing, as much as possible, to a data server.
Data server changes and switching database vendors
When designing and maintaining metadata models, the modeler must consider changes to the underlying databases or the requirements to change the database vendors altogether.