You want to create a dimensionally modeled relational model from a relational data Data Sources, references to data sources defined in Cognos Manager. Get indepth overview of different types of models i.e., relational model and DMR model in Cognos and their features in detail. Read for More!. Creating a Framework Manager Dimensional Model – DMR. 9- Import the tables/views, Known as Query Subject in Cognos world. Identify.

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There are three different types of query subjects: If the star schema is modeled in its final form, Regular Dimensions can be quickly generated by using Merge in New Regular Dimension on the relational modeoling of the Consolidation view.

As long as you create a snowflake or star schema that has relationships of many-to-one from the inside out, clean things up, denormalize it, and etc, you should be okay.

You also create model query subjects that are not generated directly from a data source, but are based on query items in other query modeling, including other model query subjects.

So it’s recommended to take the manual route.

Relational & DMR Model In Cognos | Relational Vs Dimensional Model

The cache for relational models is stored as long as the data source connection is open, which is typically 5 minutes. It is perfectly okay to combine a snowflake into a single model query subject as this would be a logical point of view of the business users. An Excel-file can be exported containing all language values.

However a more generic approach is to create embedded filters using security macro functions such as the LDAP username. Related Articles Design a list report with a date range prompts — Cognos Apr 05, We only want business users to have access to Presentation View, not Physical or Business View, but we cannot exclude Physical or Business because Presentation depends on it.


It is recommended to always choose a dialect as design language.

Creating a DMR model

This is typically the case with snowflake dimensions. A model is a collection of metadata that includes physical information and business information for one or kodelling data sources. A determinant is needed to identify levels of aggregation within the query subjects.

Granting or denying access to a package a very effective and easy way to implement a basic level of data security.

Creating a DMR model

When column names are changed in the database, only change the column names in the Data Foundation View. You can link one object to drm object in another namespace though.

The first is used for normal reporting and generates SQL that is fired to the database. Frameworks provide a mechanism that allow for OLAP styled reporting without the need of an actual physical cube. The dimensionally modeled database is ideal for reporting and is often referred to as a data warehouse.

DMR – Dimensionally Modeled Relational Model

Repeat step 5, but drag customer to the white area on the right and then at the bottom right-hand corner, click on Add to add a new Query Item. All indexed columns or columns containing business keys should be set as identifier. Model measure dimensions should be composed of only quantitative items. Data security will restrict users to modleling data they are not allowed to. Whatever solution was chosen, macro functions enable the modeler to create the proper SQL at runtime, by using the language options set by the user.


In Framework Manager, you associate security filters with users, groups, and roles whose unique identifiers are stored within the model.

You can check all of their many functions and parameters by clicking on the tabs on the lower left-hand corner, but we will cover that mmodelling other time. Uniquely identifies means that dmmr namespace has its own scope so two different namespaces can have an object with the same name and there won’t be any conflict because they do not affect one another.

Lets try this with Foodmart-reduced. The other way of querying is OLAP styled reporting based on a cube.

It provides a single point of entry for all corporate data and the tools to analyse this data. We will focus on one property setting for query item which is Usage. A multi dimensional analysis is a technique to modify the data so that users can view the data at different levels of details. However, each individual object at any level can be secured.

In the other hand, model query subjects are made from one or more data source subject queries. This package can support 2 query modes: Legacy report will continue running and new reports can be built using DQM. They represent the tables in a framework. Business users are insulated from underlying data complexity while IT maintains governance over the use of data sources.