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Fact Constellation
Fact constellation is a measure of online analytical processing, which is a collection of multiple fact tables sharing dimension tables, viewed as a collection of stars. It can be seen as an extension of the star schema. A fact constellation schema has multiple fact tables. It is also known as galaxy schema. It is widely used schema and more complex than star schema and snowflake schema. It is possible to create fact constellation schema by splitting original star schema into more star schema. It has many fact tables and some common dimension table. See also * Online analytical processing * Star schema * Snowflake schema In computing, a snowflake schema is a logical arrangement of tables in a multidimensional database such that the entity relationship diagram resembles a snowflake shape. The snowflake schema is represented by centralized fact tables which ar ... References {{Reflist Online analytical processing ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Online Analytical Processing
Online analytical processing, or OLAP (), is an approach to answer multi-dimensional analytical (MDA) queries swiftly in computing. OLAP is part of the broader category of business intelligence, which also encompasses relational databases, report writing and data mining. Typical applications of OLAP include business reporting for sales, marketing, management reporting, business process management (BPM), budgeting and forecasting, financial reporting and similar areas, with new applications emerging, such as agriculture. The term ''OLAP'' was created as a slight modification of the traditional database term online transaction processing (OLTP). OLAP tools enable users to analyze multidimensional data interactively from multiple perspectives. OLAP consists of three basic analytical operations: consolidation (roll-up), drill-down, and slicing and dicing.O'Brien, J. A., & Marakas, G. M. (2009). Management information systems (9th ed.). Boston, MA: McGraw-Hill/Irwin. Consolidat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fact Table
In data warehousing, a fact table consists of the measurements, metrics or facts of a business process. It is located at the center of a star schema or a snowflake schema surrounded by dimension tables. Where multiple fact tables are used, these are arranged as a fact constellation schema. A fact table typically has two types of columns: those that contain facts and those that are a foreign key to dimension tables. The primary key of a fact table is usually a composite key that is made up of all of its foreign keys. Fact tables contain the content of the data warehouse and store different types of measures like additive, non-additive, and semi-additive measures. Fact tables provide the (usually) additive values that act as independent variables by which dimensional attributes are analyzed. Fact tables are often defined by their ''grain''. The grain of a fact table represents the most atomic level by which the facts may be defined. The grain of a sales fact table might be stated as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dimension Table
A dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. Commonly used dimensions are people, products, place and time. (Note: People and time sometimes are not modeled as dimensions.) In a data warehouse, dimensions provide structured labeling information to otherwise unordered numeric measures. The dimension is a data set composed of individual, non-overlapping data elements. The primary functions of dimensions are threefold: to provide filtering, grouping and labelling. These functions are often described as " slice and dice". A common data warehouse example involves sales as the measure, with customer and product as dimensions. In each sale a customer buys a product. The data can be sliced by removing all customers except for a group under study, and then diced by grouping by product. A dimensional data element is similar to a categorical variable in statistics. Typically dimensions in a data warehouse are organiz ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Star Schema
In computing, the star schema is the simplest style of data mart schema and is the approach most widely used to develop data warehouses and dimensional data marts. The star schema consists of one or more fact tables referencing any number of dimension tables. The star schema is an important special case of the snowflake schema, and is more effective for handling simpler queries. The star schema gets its name from the physical model's", p. 708 resemblance to a star shape with a fact table at its center and the dimension tables surrounding it representing the star's points. Model The star schema separates business process data into facts, which hold the measurable, quantitative data about a business, and dimensions which are descriptive attributes related to fact data. Examples of fact data include sales price, sale quantity, and time, distance, speed and weight measurements. Related dimension attribute examples include product models, product colors, product sizes, geographic ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Online Analytical Processing
Online analytical processing, or OLAP (), is an approach to answer multi-dimensional analytical (MDA) queries swiftly in computing. OLAP is part of the broader category of business intelligence, which also encompasses relational databases, report writing and data mining. Typical applications of OLAP include business reporting for sales, marketing, management reporting, business process management (BPM), budgeting and forecasting, financial reporting and similar areas, with new applications emerging, such as agriculture. The term ''OLAP'' was created as a slight modification of the traditional database term online transaction processing (OLTP). OLAP tools enable users to analyze multidimensional data interactively from multiple perspectives. OLAP consists of three basic analytical operations: consolidation (roll-up), drill-down, and slicing and dicing.O'Brien, J. A., & Marakas, G. M. (2009). Management information systems (9th ed.). Boston, MA: McGraw-Hill/Irwin. Consolidat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Star Schema
In computing, the star schema is the simplest style of data mart schema and is the approach most widely used to develop data warehouses and dimensional data marts. The star schema consists of one or more fact tables referencing any number of dimension tables. The star schema is an important special case of the snowflake schema, and is more effective for handling simpler queries. The star schema gets its name from the physical model's", p. 708 resemblance to a star shape with a fact table at its center and the dimension tables surrounding it representing the star's points. Model The star schema separates business process data into facts, which hold the measurable, quantitative data about a business, and dimensions which are descriptive attributes related to fact data. Examples of fact data include sales price, sale quantity, and time, distance, speed and weight measurements. Related dimension attribute examples include product models, product colors, product sizes, geographic ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Snowflake Schema
In computing, a snowflake schema is a logical arrangement of tables in a multidimensional database such that the entity relationship diagram resembles a snowflake shape. The snowflake schema is represented by centralized fact tables which are connected to multiple dimensions. "Snowflaking" is a method of normalizing the dimension tables in a star schema. When it is completely normalized along all the dimension tables, the resultant structure resembles a snowflake with the fact table in the middle. The principle behind snowflaking is normalization of the dimension tables by removing low cardinality attributes and forming separate tables. The snowflake schema is similar to the star schema. However, in the snowflake schema, dimensions are normalized into multiple related tables, whereas the star schema's dimensions are denormalized with each dimension represented by a single table. A complex snowflake shape emerges when the dimensions of a snowflake schema are elaborate, having ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
