Category : SSAS


Role playing dimension

We have explored Junk dimension and Degenerate dimension in previous posts, now we are going to discuss Role playing dimension in this post. Lets start with the definition followed by an example.

Role playing dimension

A fact table keeps the facts of a business process. It is built of two types of columns: measure columns and dimension key columns. Measure are the quantitative business data about the business process and dimension keys reference to the dimension tables which hold the textual attributes of the business process.

Typically a dimension key column of a fact table refers a dimension table but its also very common where multiple columns of a fact table refer to a single dimension table. When a single dimension table is linked from multiple dimension key columns of a fact table, that dimension table is known as role playing dimension. As multiple columns of a fact table … More


Degenerate dimension

We have discussed the use of junk dimensions in data modelling and in this post we are going to explore Degenerate dimension. Lets start with the definition.

Degenerate Dimension

A high cardinality attribute column in the fact table which does not have any other content except its natural key and is required as a dimension for analysis or drill-down purpose, is called a degenerate dimension. As this degenerate dimension is constructed from a fact table item and is placed in the fact table, it is also known as fact dimension. It helps to reduce duplicate data by placing high cardinality dimension key in the fact table.

Degenerate dimension keys are significantly unique and are nearly as large as fact table. Moving this attribute in a single column dimension table requires a considerably large dimension table, and you would also need to join the surrogate key of the fact … More


Junk dimension 2

What is a Junk Dimension? Have you ever come across a scenario where many small dimension tables connect (using foreign key) to the fact table? In data warehouse, we have two types of tables, Fact and Dimension. Fact table contains business facts as measures and references to the dimension tables. Dimension tables have attributes which contains textual information of business facts and are used to filter and label the data.

Typically, fact tables are deeper whereas dimension tables are wider. Sometimes it happens that we have many narrow and low cardinality (low cardinality : few number of rows in the table) dimensions in the system; like flags and indicators. To keep all these information in fact table, we need to connect all these dimension tables (available in system or created from flag and indicator attributes) with fact table. Connecting all these small dimension tables converts fact table in … More


SQL Server 2012 Multidimensional vs tabular

Which model should you use, Multidimensional vs Tabular?

Well, there is no clear-cut answer, but there are some factors that can make you choose one over the other:

  • If you want to use DAX, you have to use Tabular
  • If you want to use Power View, you have to use Tabular
  • If your dataset is extremely large, go with Multidimensional
  • If you need writeback support, you have to use Multidimensional
  • If you need access to many different external data sources, choose Tabular
  • If you need complex calculations, scoping, and named sets, choose Multidimensional
  • If you need extreme speed and consistently fast query time, choose Tabular
  • If you need Many-to-Many relationships, choose Multidimensional (can be done in Tabular but difficult)
  • If your solution requires complex modeling, choose Multidimensional
  • If you need any of the following features, you must use Multidimensional: Actions, Custom Assemblies, Custom Rollups, Custom Drillthrough Actions (but BIDS Helper
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