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Data warehouse Mehrshad Mirshekari Autumn 85

Outline. IntroductionHistory of DWDefinitionCharacteristics of DWData Warehouse Architectures ETL process. Introduction. Different types of data processing:data processing in organizations can be viewed either as : Transactional Analytical. Introduction. Transactional data processing:

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Data warehouse Mehrshad Mirshekari Autumn 85

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    2. Outline Introduction History of DW Definition Characteristics of DW Data Warehouse Architectures ETL process

    3. Introduction Different types of data processing: data processing in organizations can be viewed either as : Transactional Analytical

    4. Introduction Transactional data processing: High-volume and easy-processing collections of data that generate by organizations everyday. Analytical data processing: Analysis of accumulated data frequently by end users; also referred to as business intelligence, includes data mining decision support systems (DSSs), enterprise information systems, web applications, querying, and other end-user activities.

    5. Introduction Today organizations use DW to store analytical data in order to place strategic information in the hands of decision makers to aid productivity and empower users for making better decisions, leading to greater competitive advantage .

    6. History of DW Data Warehouses became a distinct type of computer database during the late 1980s and early 1990s. They were developed to meet a growing demand for management information and analysis that could not be met by operational systems. Operational systems were unable to meet this need for a range of reasons: The processing load of reporting reduced the response time of the operational systems, The database designs of operational systems were not optimized for information analysis and reporting, Most organizations had more than one operational system, so company-wide reporting could not be supported from a single system, and Development of reports in operational systems often required writing specific computer programs which was slow and expensive

    7. Definition A DW is a subject oriented, integrated, time variant and non volatile collection of data in support of management’s decision making process. A data warehouse is the main repository of the organization's historical data, its corporate memory.

    8. Characteristics of a DW Subject oriented Integrated Time Variant Non-Volatile Consistency Web-based

    9. Data Warehouse Architectures Generic Two-Level Architecture Independent Data Mart Dependent Data Mart and Operational Data Store Logical Data Mart and @ctive Warehouse

    14. Thank you for your attention Any question???

    15. The ETL Process Capture Scrub or data cleansing Transform Load and Index

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