Contents
What is the difference between fact and dimension table?
A fact table works with dimension tables. A fact table holds the data to be analyzed, and a dimension table stores data about the ways in which the data in the fact table can be analyzed. Thus, the fact table consists of two types of columns.
Can a fact table be a dimension?
As a rule, each foreign key of the fact table must have its counterpart in a dimension table. This means that every table in a dimensional database that expresses a many-to-many relationship is a fact table. Therefore a dimension table can also be a fact table for a separate star schema.
How do dimension tables differ from fact tables within a data warehouse environment?
Fact tables are the large tables in your data warehouse schema that store business measurements. Dimension tables store the information you normally use to contain queries. Dimension tables are usually textual and descriptive and you can use them as the row headers of the result set.
How do you create a fact table?
Use the wizard to create the corresponding fact and dimension tables.
- In Data Modeler, lock the model for editing.
- In the Database menu in the left pane, right-click the source table that contains the fact and dimensional data that you want to model, select Add to Model, and then select Add as Fact and Dimension Tables.
Why do we need fact and dimension table?
Fact table contains measurements, metrics, and facts about a business process while the Dimension table is a companion to the fact table which contains descriptive attributes to be used as query constraining. Fact table helps to store report labels whereas Dimension table contains detailed data.
What is the primary key of a fact table?
The fact table’s primary key is made up of the primary keys of all the dimension tables. The primary key of the REVENUE fact table, which is a concatenation of the primay keys of the dimension tables, can uniquely identify each row.
What’s the difference between fact table and dimension table?
Fact tables comprises of the facts of the system as its data content, and Dimension tables comprises of all the properties or objects of the fact tables that can help to connect fact tables to the respective dimension tables. The data in both the tables can be in normal text format, while fact tables can have numbers along with the texts.
How is a fact table used in a data warehouse?
Summary: in this tutorial, we will discuss fact table, fact table types and four steps of designing a fact table in dimensional data model described by Kimball. A fact table is used in the dimensional model in data warehouse design. A fact table is found at the center of a star schema or snowflake schema surrounded by dimension tables.
Where do we store measurements in fact tables?
Fact tables are where we store these measurements. They hold business data that can be aggregated across dimension combinations. But the fact is that fact tables are not so easily described – they have flavors of their own. In this article, we’ll answer some basic questions about fact tables, and examine the pros and cons of each type.
What are the steps to designing a fact table?
Here is overview of four steps to designing a fact table described by Kimball: Choosing business process to model – The first step is to decide what business process to model by gathering and understanding business needs and available data Declare the grain – by declaring a grain means describing exactly what a fact table record represents