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2. Template:Data warehouses - Wikipedia

   en.wikipedia.org/wiki/Template:Data_warehouses

   To change this template's initial visibility, the |state= parameter may be used: {{Data warehouses | state = collapsed}} will show the template collapsed, i.e. hidden apart from its title bar. {{Data warehouses | state = expanded}} will show the template expanded, i.e. fully visible.

3. Wrapper (data mining) - Wikipedia

   en.wikipedia.org/wiki/Wrapper_(data_mining)

   Structured data are typically descriptions of objects retrieved from underlying databases and displayed in web pages following fixed templates at a low level, injected into pages where the high-level structure can vary from week to week, per the rapidly evolving fashion of the site's presentation skin.

4. Microsoft Office 2001 - Wikipedia

   en.wikipedia.org/wiki/Microsoft_Office_2001

   Makes it possible to have PowerPoint presentations made into real slides, or transparencies, among other printed media. This wizard facilitates the process of sending PowerPoint presentations to Genigraphics who will create the product that you want. [6] Microsoft Query Collects data from outside sources and brings it together in an Excel document.

5. Data warehouse - Wikipedia

   en.wikipedia.org/wiki/Data_warehouse

   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 ...

6. Data mart - Wikipedia

   en.wikipedia.org/wiki/Data_mart

   Data Warehouse and Data Mart overview, with Data Marts shown in the top right.. A data mart is a structure/access pattern specific to data warehouse environments. The data mart is a subset of the data warehouse that focuses on a specific business line, department, subject area, or team. [1]

7. Database model - Wikipedia

   en.wikipedia.org/wiki/Database_model

   A data warehouse can contain multiple dimensional schemas that share dimension tables, allowing them to be used together. Coming up with a standard set of dimensions is an important part of dimensional modeling. Its high performance has made the dimensional model the most popular database structure for OLAP.