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The common warehouse metamodel (CWM) defines a specification for modeling metadata for relational, non-relational, multi-dimensional, and most other objects found in a data warehousing environment. The specification is released and owned by the Object Management Group , which also claims a trademark in the use of "CWM".
Logo. CityGML is an open standardised data model and exchange format to store digital 3D models of cities and landscapes.It defines ways to describe most of the common 3D features and objects found in cities (such as buildings, roads, rivers, bridges, vegetation and city furniture) and the relationships between them.
MEAN (MongoDB, Express.js, AngularJS (or Angular), and Node.js) [1] is a source-available JavaScript software stack for building dynamic web sites and web applications. [2] A variation known as MERN replaces Angular with React.js front-end, [3] [4] and another named MEVN use Vue.js as front-end.
Data warehouse automation (DWA) refers to the process of accelerating and automating the data warehouse development cycles, while assuring quality and consistency. DWA is believed to provide automation of the entire lifecycle of a data warehouse, from source system analysis to testing to documentation .
Angular 2.0 was announced at the ng-Europe conference 22–23 October 2014. [16] On April 30, 2015, the Angular developers announced that Angular 2 moved from Alpha to Developer Preview. [17] Angular 2 moved to Beta in December 2015, [18] and the first release candidate was published in May 2016. [19] The final version was released on 14 ...
Data Warehouse and Data mart overview, with Data Marts shown in the top right. 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 a core component of business intelligence. [1] Data warehouses are central repositories of data integrated from ...
The Kimball lifecycle is a methodology for developing data warehouses, and has been developed by Ralph Kimball and a variety of colleagues. The methodology "covers a sequence of high level tasks for the effective design, development and deployment" of a data warehouse or business intelligence system. [1]
The single most dramatic way to affect performance in a large data warehouse is to provide a proper set of aggregate (summary) records that coexist with the primary base records. Aggregates can have a very significant effect on performance, in some cases speeding queries by a factor of one hundred or even one thousand.