Data Warehouse Software

Data Warehouse Software

Huanyu Ouyang (People’s Hospital of Jangxi Province, China) and John Wang (Montclair State University, USA)
Copyright: © 2008 |Pages: 6
DOI: 10.4018/978-1-59904-881-9.ch029
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Abstract

A data warehouse (DW) is a complete intelligent data storage and information delivery or distribution solution enabling users to customize the flow of information through their organization (Inmon & Hackathorn, 2002). It provides all authorized members of users’ organization with flexible, secure, and rapid access to critical information and intelligent reporting. DW can extract information from sources anywhere in the world and then delivers intelligence anywhere in the world. It connects to any platform, database, data source, and it will also scale to businesses and applications of any size. As early as the 1970’s, data warehousing software (DWS) was recognized when the earliest systems were first developed. The database designs of operational systems were not effective enough for the information analysis and reporting (The Data Warehousing Information Center, 2006).

Key Terms in this Chapter

Real-Time Data Warehouse: Data warehouses at this stage are updated on a transaction or event basis, every time an operational system performs a transaction.

Integrated Data Warehouse: Data warehouses at this stage are used to generate activity or transactions that are passed back into the operational systems for use in the daily activity of the organization.

Online Transaction Processing (OLTP): Handles real-time transactions which inherently have some special requirements.

Extraction, Transformation, and Loading (ETL): Extract, transform, and load data from across the enterprise to create consistent, accurate information.

Business Intelligence (BI): A broad category of application programs and technologies for gathering, storing, analyzing, and providing access to data to help enterprise users make better business decisions. BI applications include the activities of decision support, query and reporting, OLAP, statistical analysis, forecasting, and data mining.

Online Analytical Processing (OLAP): A broad term to describe a type of processing that allows for unlimited views of multiple relationships within summarized data. It is typically, although not necessarily, associated with multi-dimensional databases where this pre-summarized data can be efficiently stored.

SQL Server: SQL Server is a relational database management system (RDBMS) produced by Microsoft.

Petabyte: Equal to approximately 1,000 terabytes.

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