In data warehouse, dimension and index are two important concepts.
Dimension (Dimension):
Dimension is a method to describe various attributes in the business process, which is used to analyze and classify the business process. Dimensions include various business attributes such as time, location, personnel, products, and customers, and are the basis of data analysis.
Measure:
The measure is a standard for measuring the effect of a business process and an important indicator for data analysis. Indicators include quantity, amount, time, ratio, percentage, etc., and are used to measure various results of a business process.
In a data warehouse, dimension tables and index tables are usually used for data storage and query. The relationship between the two is as follows:
Dimension Table:
A dimension table is a table used to store dimension data, usually including the primary key of the dimension table, dimension attributes and some description information. In a data warehouse, a dimension table usually has a primary key that is used to relate it to a fact table. The role of the dimension table is to provide dimension attributes to help users analyze business processes.
Fact Table:
Fact Table is a table used to store indicator data. It usually includes the primary key, indicators and some description information of the indicator table. In data warehouses, indicator tables also usually have a primary key that is used to associate with dimension tables. The function of the indicator table is to provide various indicators of the business process and help users analyze the results of the business process.
Usually, the dimension table and the indicator table are related by the primary key to form the fact table. The fact table is the core part of the data warehouse. It is used to store various index data and dimension attributes of the business process, and is an important basis for data analysis.
In data warehouse, fact table (Fact Table) and dimension table (Dimension Table) are two very important concepts. Their status and use in data warehouse are as follows:
Fact table:
The fact table is one of the most important tables in the data warehouse, which is used to store various indicator data of the business process. It is organized according to time and business processes, and usually includes a large number of records and indicators. Different fact tables can be designed according to different business processes. In a data warehouse, there are usually multiple fact tables used to store indicator data for different business processes. The design of the fact table needs to consider the granularity and hierarchical structure of the index, as well as factors such as data storage and query efficiency.
Dimension table:
A dimension table is a table used to store various attribute values of a business process. It includes various attributes, characteristics and dimensions used to describe business processes, such as time, place, people, products, customers, etc. Dimension tables usually include dimension attributes and dimension-related information, such as dimension names, identifiers, descriptions, superior-subordinate relationships, etc. The design of dimension tables needs to consider factors such as the attributes and characteristics of the business process, as well as data storage and query efficiency.
Status in the data warehouse:
The fact table and the dimension table are the two most important parts in the data warehouse and one of the core elements of the data warehouse. The fact table is used to store various indicator data of the business process, while the dimension table is used to provide various attributes and characteristics of the business process to help users analyze the business process. Fact tables and dimension tables are usually associated through primary keys, forming one of the basic structures of a data warehouse.
Usage:
Fact tables and dimension tables are the two basic tables in data warehouses. They are usually designed based on business processes. In practical applications, we can design and build fact tables and dimension tables according to business needs to facilitate users' data analysis and decision-making. For example, in the sales field, we can design different fact tables and dimension tables based on different sales processes to facilitate analysis of sales business results and trends.