Dimension in Tableau
Dimension in Tableau are fields that are used to slice and describe data records and it contains Primary key (Pk) and Textual information. Dimensions in Tableau are divided into 9 different types.
- Slowly changing dimension: If the data in the dimension are changing over the period of time, then such a kind of dimension is called as SCD. Example: – In employ dimension data will change over a period of time.
- Rapidly Changing dimension: If the data is changing rapidly then such kind of dimension is called a rapidly changing dimension. Example:- Age change from time to time.
- Unchanged dimension: If the data is constant and it won’t change then it is called as an unchanged dimension or static dimension. Example:- Traffic signals, surname etc.
- Conformed dimension: It is a dimension which is shared by the multiple business areas. Example: Java, DWH, Oracle etc.
- Shrunken dimension: Subset of one dimension or subpart of one dimension is called as a shrunken dimension.Example: Quarter is the shrunken dimension of the year.
- Role-playing dimension: Once dimension is playing multiple roles in the fact table is called as a role-playing dimension. Example: Take data dimension, the date dimension contains data of order, date of delivery, date of invoice etc.
- Degenerated dimension: It is a dimension, where all the values get stored in a fact table, not in a separate dimension table. Degenerated dimension always contains the dimension keys, it won’t contain any other values.
- Junk dimension: Junk dimension is a dimension where we store Junk data. It is a single table with a combination of different related and unrelated data values like flags, indicators, some other unwanted data. A Junk dimension is mainly used to avoid the large no of foreign keys in the fact table.
- Informed dimensions: Here all the dimensions are attached to fact. If we want to load employ table to the fact, it would be done by surrogate key.
Measures in Tableau
Depending on the measure values the Facts or measures in Tableau are three types, Additive fact, Semi-additive fact, Non-additive fact.
- Additive fact: It is a type of fact where it supports all the group functions (Sum, min, max, Avg etc.)
- Semi-additive fact: It is a fact which supports only a few of the group functions. Example: For account balance, we can apply only Max and Min which gives the meaningful output.
- Non-additive fact: It is a type of measure where we can’t apply any type of aggregations. Example: we will take rations, percentages we can’t apply any group functions.