9/10/2023 0 Comments Data warehouse architectureCentral data warehouse should consist of database staging or known as operational data store as an intermediate stage for operational processing of data integration before transform into the data warehouse. This architecture has only one data model which are consistent and complete from all data sources. This architecture copies and stores heterogeneous operational and external data to a single and consistent data warehouse. Centralized Data Warehouse Architecture – Central data warehouse architecture build based on hub-and-spoke architecture but without the dependent data mart component.Hub and spoke mainly focused on building a scalable and maintainable infrastructure for data warehouse. Hub-and-spoke Architecture – The hub is the central server taking care of information exchange and the spoke handle data transformation for all regional operation data stores.This allows the data warehouse to functions more in virtual mode and combined all data marts and process as one data warehouse. Bus architecture allows data marts not only located in one server but it can be also being located on different server. Data Mart Bus Architecture – The design and architecture of data warehouse with unions of data marts which are known as the bus architecture or virtual data warehouse.Since every organizational units tend to build their own database which operates as independent data mart, it is best used as an ad-hoc data warehouse and also to be use as a prototype before building a real data warehouse. Thus, it complicates cross data mart analysis. This type of data mart is simple yet consists of different form that was derived from multiple design structures from various inconsistent database designs. It is mainly used by departments, divisions of company to provide individual operational databases. Independent Data Marts – Independent data marts also known as localized or small scale data warehouse.William Inmon and Ralph Kimball Data Warehouse Differences: Both believed that dependent data warehouse architecture is necessary to fulfil the requirement of enterprise end users in term of preciseness, timing and data relevancy The role of database staging and ETL (extract, transform and loading) processes on data are inevitable components in both researchers data warehouse design. The data warehouse is the collections of data marts combine into one central repository.Īlthough Inmon and Kimball have a different design view of data warehouse, they do agree on successful implementation of data warehouse that depends on an effective collection of operational data and validation of data mart. Kimball’s views data warehouse as a unions of data marts. Inmon’s data warehouse model splits data marts as a copy and distributed as an interface between data warehouse and end users. Inmon’s data warehouse architecture strategy is different from Kimball’s. Inmon defined data warehouse as a dependent data mart structure while Kimball defined data warehouse as a bus based data mart structure.Ī data warehouse is a read-only data source where end-users are not allowed to change the values or data elements. But they have different perspectives on data warehouse in term of design and architecture. The main proponents of data warehouse are William Inmon and Ralph Kimball. Thus, critical decision making process of this dataset needs suitable data warehouse model. The evolution of data in data warehouse can provide multiple dataset dimensions to solve various problems. The emergence of cross discipline domain such as knowledge management in finance, health and e-commerce have proved that vast amount of data need to be analyzed. These technologies include relational and MDDB management systems, client/server architecture, meta-data modelling and repositories, graphical user interface and much more. This historical data is used for analysis that supports business decisions at many levels, from strategic planning to performance evaluation of a discrete organizational unit. It provides an effective integration of operational databases into an environment that enables strategic use of data. Data warehouse is a database containing data that usually represents the business history of an organization. According to William Inmon, data warehouse is a subject-oriented, integrated, time-variant, and non-volatile collection of data in support of the management’s decision-making process.
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