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Early-arriving Fact
In the data warehouse practice of extract, transform, load (ETL), an early fact or early-arriving fact, also known as late-arriving dimension or late-arriving data, denotes the detection of a dimensional natural key during fact table source loading, prior to the assignment of a corresponding primary key In the relational model of databases, a primary key is a ''specific choice'' of a ''minimal'' set of attributes (Column (database), columns) that uniquely specify a tuple (Row (database), row) in a Relation (database), relation (Table (database), t ... or surrogate key in the dimension table. Hence, the fact which cites the dimension arrives early, relative to the definition of the dimension value. An example could be backdating or making corrections to data. Handling Procedurally, an early fact can be treated several ways: * As an error: On the presumption that the dimensional attribute values should have been collected before fact source loading * As a valid fact, pause lo ... [...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 reporting and data analysis and is considered a core component of business intelligence. DWs are central repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise. The data stored in the warehouse is uploaded from the 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 DW for reporting. Extract, transform, load (ETL) and extract, load, transform (ELT) are the two main approaches used to build a data warehouse system. ETL-based data warehousing The typical extract, transform, load (ETL)-based data warehouse uses staging, data integration, and access lay ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Extract, Transform, Load
In computing, extract, transform, load (ETL) is a three-phase process where data is extracted, transformed (cleaned, sanitized, scrubbed) and loaded into an output data container. The data can be collated from one or more sources and it can also be outputted to one or more destinations. ETL processing is typically executed using software applications but it can also be done manually by system operators. ETL software typically automates the entire process and can be run manually or on reoccurring schedules either as single jobs or aggregated into a batch of jobs. A properly designed ETL system extracts data from source systems and enforces data type and data validity standards and ensures it conforms structurally to the requirements of the output. Some ETL systems can also deliver data in a presentation-ready format so that application developers can build applications and end users can make decisions. The ETL process became a popular concept in the 1970s and is often used in d ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Natural Key
A natural key (also known as business key or domain key) is a type of unique key in a database formed of attributes that exist and are used in the external world outside the database (i.e. in the business domain or domain of discourse). In the relational model of data, a natural key is a superkey and is therefore a functional determinant for all attributes in a relation. A natural key serves two complementary purposes: it provides a means of identification for data and it imposes a rule, specifically a ''uniqueness constraint'', to ensure that data remains unique within an information system. The uniqueness constraint assures uniqueness of data within a certain technical context (e.g. a set of values in a table, file or relation variable) by rejecting input of any data that would otherwise violate the constraint. This means that the user can rely on a guaranteed correspondence between facts identified by key values recorded in a system and the external domain of discourse (a sing ... [...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 state ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Primary Key
In the relational model of databases, a primary key is a ''specific choice'' of a ''minimal'' set of attributes (columns) that uniquely specify a tuple (row) in a relation ( table). Informally, a primary key is "which attributes identify a record," and in simple cases constitute a single attribute: a unique ID. More formally, a primary key is a choice of candidate key (a minimal superkey); any other candidate key is an alternate key. A primary key may consist of real-world observables, in which case it is called a '' natural key'', while an attribute created to function as a key and not used for identification outside the database is called a '' surrogate key''. For example, for a database of people (of a given nationality), time and location of birth could be a natural key. National identification number is another example of an attribute that may be used as a natural key. History Although mainly used today in the relational database context, the term "primary key" pre-dates ... [...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 su ... [...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 or ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Business Intelligence Terms
Business is the practice of making one's living or making money by producing or buying and selling products (such as goods and services). It is also "any activity or enterprise entered into for profit." Having a business name does not separate the business entity from the owner, which means that the owner of the business is responsible and liable for debts incurred by the business. If the business acquires debts, the creditors can go after the owner's personal possessions. A business structure does not allow for corporate tax rates. The proprietor is personally taxed on all income from the business. The term is also often used colloquially (but not by lawyers or by public officials) to refer to a company, such as a corporation or cooperative. Corporations, in contrast with sole proprietors and partnerships, are a separate legal entity and provide limited liability for their owners/members, as well as being subject to corporate tax rates. A corporation is more complicated a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
