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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] |
Surrogate Key
A surrogate key (or synthetic key, pseudokey, entity identifier, factless key, or technical key) in a database is a unique identifier for either an ''entity'' in the modeled world or an ''object'' in the database. The surrogate key is ''not'' derived from application data, unlike a ''natural'' (or ''business'') key. Definition There are at least two definitions of a surrogate: ; Surrogate (1) – Hall, Owlett and Todd (1976): A surrogate represents an ''entity'' in the outside world. The surrogate is internally generated by the system but is nevertheless visible to the user or application. ; Surrogate (2) – Wieringa and De Jonge (1991): A surrogate represents an ''object'' in the database itself. The surrogate is internally generated by the system and is invisible to the user or application. The ''Surrogate (1)'' definition relates to a data model rather than a storage model and is used throughout this article. See Date (1998). An important distinction between a s ... [...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] |
Reverse Star Schema
The reverse star schema is a schema optimized for fast retrieval of large quantities of descriptive data. The design was derived from a warehouse star schema, and its adaptation for descriptive data required that certain key characteristics of the classic star schema be "reversed". Model The relation of the central table to those in dimension tables is one-to-many, or in some cases many-to-many rather than many-to-one; the primary keys of the central table are the foreign keys in dimension tables, and the main tables are, in general, smaller than the dimension tables. Main table columns are typically the source of query constraints, as opposed to dimension tables in the classical star schema. By starting queries with the smaller table, many results are filtered out early in the querying process, thereby streamlining the entire search path. To add further flexibility, more than one main table is allowed, with main and submain tables having a one-to-many relation. Each main tab ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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] |
Data Warehouse
In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for Business intelligence, reporting and data analysis and is a core component of business intelligence. Data warehouses are central Repository (version control), repositories of data integrated from disparate sources. They store current and historical data organized in a way that is optimized for data analysis, generation of reports, and developing insights across the integrated data. They are intended to be used by analysts and managers to help make organizational decisions. The data stored in the warehouse is uploaded from operational systems (such as marketing or sales). The data may pass through an operational data store and may require data cleansing for additional operations to ensure data quality before it is used in the data warehouse for reporting. The two main workflows for building a data warehouse system are extract, transform, load (ETL) and extract, load, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ROLAP
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. Consolidation ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
OLAP Cube
An OLAP cube is a multi-dimensional array of data. Online analytical processing (OLAP) is a computer-based technique of analyzing data to look for insights. The term ''cube'' here refers to a multi-dimensional dataset, which is also sometimes called a hypercube if the number of dimensions is greater than three. Terminology A cube can be considered a multi-dimensional generalization of a two- or three-dimensional spreadsheet. For example, a company might wish to summarize financial data by product, by time-period, and by city to compare actual and budget expenses. Product, time, city and scenario (actual and budget) are the data's dimensions. ''Cube'' is a shorthand for ''multidimensional dataset'', given that data can have an arbitrary number of ''Dimension (data warehouse), dimensions''. The term hypercube is sometimes used, especially for data with more than three dimensions. A cube is not a "cube" in the strict mathematical sense, as the sides are not all necessarily equal. ... [...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] |
Database Normalization
Database normalization is the process of structuring a relational database in accordance with a series of so-called '' normal forms'' in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model. Normalization entails organizing the columns (attributes) and tables (relations) of a database to ensure that their dependencies are properly enforced by database integrity constraints. It is accomplished by applying some formal rules either by a process of ''synthesis'' (creating a new database design) or ''decomposition'' (improving an existing database design). Objectives A basic objective of the first normal form defined by Codd in 1970 was to permit data to be queried and manipulated using a "universal data sub-language" grounded in first-order logic. An example of such a language is SQL, though it is one that Codd regarded as seriously flawed. The objectives of normalization ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Surrogate Key
A surrogate key (or synthetic key, pseudokey, entity identifier, factless key, or technical key) in a database is a unique identifier for either an ''entity'' in the modeled world or an ''object'' in the database. The surrogate key is ''not'' derived from application data, unlike a ''natural'' (or ''business'') key. Definition There are at least two definitions of a surrogate: ; Surrogate (1) – Hall, Owlett and Todd (1976): A surrogate represents an ''entity'' in the outside world. The surrogate is internally generated by the system but is nevertheless visible to the user or application. ; Surrogate (2) – Wieringa and De Jonge (1991): A surrogate represents an ''object'' in the database itself. The surrogate is internally generated by the system and is invisible to the user or application. The ''Surrogate (1)'' definition relates to a data model rather than a storage model and is used throughout this article. See Date (1998). An important distinction between a s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
