Business intelligent architecture system and method
The present disclosure describes a standardized logical model architecture, for use in building a business intelligent systems, and a system and method of using the logical model architecture to populate a data repository (e.g., a data mart/warehouse) with the data to satisfy reporting and data analysis needs.
1. A method comprising:
defining, via a computing device, a first interface of a logical model architecture comprising one or more granular dimensions and measures associated with a data item;
defining, via the computing device, a second interface of said logical model architecture comprising metrics and associations between said metrics and said one or more granular dimensions and measures;
defining, via the computing device, a third interface of said logical model architecture comprising a plurality of user data requirements corresponding to a relationship between said metrics and at least one of said granular dimensions and measures;
defining, a first set of transformations of said logical model architecture via the computing device, comprising one or more transformations to map source data items to said one or more granular dimensions and measures of said first interface;
defining, a second set of transformations of said logical model architecture via the computing device, each transformation of said second transformation set corresponding to at least one of said user data requirements and communicated to a data repository maintained on a computer-readable storage medium, each defined transformation utilized for populating the data repository with data to satisfy said corresponding user data requirement;
determining, via the computing device, a volume of data being stored in response to said second set of transformations; and
storing, via the computing device in the data repository, the associations between said metrics and said one or more granular dimensions and measures based at least in part on the determined volume.
2. The method of claim 1 , wherein said second set of transformations is used to generate a schema for said data repository.
3. The method of claim 2 , wherein the schema is a relational database schema.
4. The method of claim 1 , wherein said logical model architecture is an enterprise-wide logical model architecture.
5. The method of claim 1 , wherein said first, second and third interfaces and said first and second transformations are defined using metadata, said metadata being stored in a metadata repository.
6. The method of claim 5 , wherein said metadata repository is accessed to retrieve information about said logical model architecture using an application programming interface (API).
7. The method of claim 1 , wherein the associations between said metrics and said one or more granular dimensions and measures is stored in the data repository based at least in part on a determined volume of data being stored in response to said second set of transformations.