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Data warehouses (DWs) are databases used by decision makers to analyze the status and the development of an organization. DWs are based on large amounts of data integrated from heterogeneous sources into multidimensional databases, and they are optimized for accessing data in a way that comes naturally to human analysts (e.g., OLAP applications).
The bus matrix purpose is one of high abstraction and visionary planning on the data warehouse architectural level. By dictating coherency in the development and implementation of an overall data warehouse the bus architecture approach enables an overall vision of the broader enterprise integration and consistency while at the same time dividing the problem into more manageable parts [2 ...
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]
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 ...
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As an offline reader, Kiwix works with a library of contents that are zim files: you can pick & choose whichever Wikimedia project (Wikipedia in any language, Wiktionary, Wikisource, etc.), as well as TED Talks, PhET Interactive Maths & Physics simulations, Project Gutenberg, etc. It is free and open source, and currently available for download on:
A data management plan or DMP is a formal document that outlines how data are to be handled both during a research project, and after the project is completed. [1] The goal of a data management plan is to consider the many aspects of data management, metadata generation, data preservation, and analysis before the project begins; [2] this may lead to data being well-managed in the present ...
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.
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