Ssas relationship

Lesson 5: Defining Relationships Between Dimensions and Measure Groups | Microsoft Docs

ssas relationship

SQL Server Analysis Services yes Azure Analysis Services. In tabular models, a relationship is a connection between two tables of data. July 15, devinknight SSAS Leave a comment This relationship type would be used when a dimension has no relationship to a measure. SSAS dimension designer has introduced one more tab called “ AttributeRelationships” to simplify the process of setting relationships.

But beware that incorrectly defined attribute relationship can cause illogical query results.

ssas relationship

The following figure exhibits the Attribute Relationship tab for the Product dimension. The Attribute relationship designer has three panes, Design pane — shows the graphical representation of the attribute relationship that is defined between the selected attributes. Attributes pane — shows the available attributes that are selected from the Product dimension tables.

Attributes to relationships

Attribute Relationships pane — shows the relationships set between the attributes. Size attribute has a many-to-one relationship with the Size Range attribute. The importance of Attribute Relationship Attribute relationship is important in the dimension design as it provides the following benefits, It takes less time for processing dimension, partition and query by reducing the amount of memory required for processing.

Increased query performance by faster storage access and optimized query execution plans.

ssas attribute relationships tab

The table contains attribute information not only for each line of an order issued by a reseller, but about the order itself. The attributes circled in the previous diagram identify the information in the FactResellerSales table that could be used as attributes in a dimension.

ssas relationship

In this case, two additional pieces of information, the carrier tracking number and the purchase order number issued by the reseller, are represented by the CarrierTrackingNumber and CustomerPONumber attribute columns. This information is interesting-for example, users would definitely be interested in seeing aggregated information, such as the total product cost, for all the orders being shipped under a single tracking number.


But, without a dimension data for these two attributes cannot be organized or aggregated. In theory, you could create a dimension table that uses the same key information as the FactResellerSales table and move the other two attribute columns, CarrierTrackingNumber and CustomerPONumber, to that dimension table.

However, you would be duplicating a significant portion of data and adding unnecessary complexity to the data warehouse to represent just two attributes as a separate dimension. Note Fact dimensions are frequently used to support drillthrough actions. Note Fact dimensions must be incrementally updated after every update to the measure group that is referenced by the fact relationship.

  • Dimension Relationships
  • Understanding Analysis Services Relationships using Dimension Usage
  • SQL Server Analysis Services Attribute Relationships

If the fact dimension is a ROLAP dimension, the Analysis Services processing engine drops any caches and incrementally processes the measure group. Many to Many Dimension Relationships In most dimensions, each fact joins to one and only one dimension member, and a single dimension member can be associated with multiple facts.

Understanding Analysis Services Relationships using Dimension Usage – Devin Knight

In relational database terminology, this is referred to as a one-to-many relationship. However, it is frequently useful to join a single fact to multiple dimension members.

Referenced the dimension is joined to an intermediate table prior to being joined to the fact table. Referenced relationship resembles a snowflake dimension, but is slightly different.

Lesson 5: Defining Relationships Between Dimensions and Measure Groups

Suppose you have a customer dimension and a sales fact; you'd like to examine total sales by customer, but you also want to examine line item sales by customer. Instead of duplicating the customer key in the line item fact table you can treat the sales fact as an intermediate table to join customer to line item. Many-to-many this option involves two fact tables and two dimension tables.

Dimension A is joined to an intermediate fact A, which in turn joins to dimension B to which the fact B is joined. Much like with fact option if you need to use many-to-many option your design could probably use some improvement. This type of relationship is sometimes necessary if you are building cubes on top of a relational database that is in 3rd normal form.