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Fact Constellation
A fact constellation schema, also referred to as a galaxy schema, is a model using multiple fact tables and multiple dimension tables. These schemas are implemented for complex data warehouses. The fact constellation is a measure of online analytical processing and can be seen as an extension of the star schema. A fact constellation schema has multiple fact tables. It is a widely used schema and more complex than star schemas and snowflake schemas. It is possible to create a fact constellation schema by splitting the original star schema into more star schemas. It has many fact tables and some common dimension tables. See also * Online analytical processing In computing, online analytical processing (OLAP) (), is an approach to quickly answer multi-dimensional analytical (MDA) queries. The term ''OLAP'' was created as a slight modification of the traditional database term online transaction proces ... * Snowflake schema References Online analytical processing {{d ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fact Table
In data warehousing, a fact table consists of the measurements, metrics or Fact (data warehouse), 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 data grain, grain. The grain of a fact table represents the most atomic level by which the facts may be defined. The grain of a sales ... [...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 orga ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Online Analytical Processing
In computing, online analytical processing (OLAP) (), is an approach to quickly answer multi-dimensional analytical (MDA) queries. The term ''OLAP'' was created as a slight modification of the traditional database term online transaction processing (OLTP). 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. OLAP tools enable users to analyse 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. Consolida ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Star Schema
In computing, the star schema or star model is the simplest style of data mart Logical schema, 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 (data warehouse), 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 data model, physical model'sC J Date, "An Introduction to Database Systems (Eighth Edition)", p. 708 resemblance to a Star polygon, 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, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Online Analytical Processing
In computing, online analytical processing (OLAP) (), is an approach to quickly answer multi-dimensional analytical (MDA) queries. The term ''OLAP'' was created as a slight modification of the traditional database term online transaction processing (OLTP). 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. OLAP tools enable users to analyse 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. Consolida ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Snowflake Schema
In computing, a snowflake schema or snowflake model is a Logical schema, logical arrangement of tables in a multidimensional database such that the Entity-relationship model, entity relationship diagram resembles a snowflake shape. The snowflake schema is represented by centralized fact tables which are connected to multiple Dimension (data warehouse), 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 Normalization (database), normalized into multiple related tables, whereas the star schema's dimensions are denormalized with each dimension represented by ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
