1 / 12

The Data Warehouse

The Data Warehouse. from William H. Inmon, Building the Data Warehouse (4 th ed). Data Warehouse =. architecture (not a technology) example of Decision Support System. Data Placement. DSS - Decision Support Systems (analytical function) OLTP – Online Transactional Processing

talor
Download Presentation

The Data Warehouse

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The Data Warehouse from William H. Inmon, Building the Data Warehouse (4th ed)

  2. Data Warehouse = architecture (not a technology) example of Decision Support System

  3. Data Placement • DSS - Decision Support Systems (analytical function) • OLTP – Online Transactional Processing (operational function) • Archival data – cheaper/slower storage

  4. primitive data operational day-to-day clerical function non-redundant non-integrated run repetitively derived data analytical historical managerial function redundant data integrated run heuristically OLTP DSS

  5. A Definition: “A data warehouse is a subject-oriented, integrated, non-volatile, and time-variant collection of data in support of management’s decisions.” (a sophisticated series of snapshots…)

  6. Design Decisions • Granularity - level of detail or summarization of the units of data in the data warehouse (more detail = lower level of granularity) • Partitioning – breakup of data into separate physical units that can be handled independently

  7. Major Components • Design of Data Warehouse itself • Interface from operational systems -role of extract (ETL) software [Extract/Transform/Load] -element of time (compound keys) -data purging

  8. Indirect Use of Data Warehouse Data An analysis program periodically spins off a file to the operational environment that includes specific summarized data Airline commission example Retail personalization example Credit scoring example

  9. Data Warehouse Requirements • Manage large amounts of data • Manage data on diverse media • Easily index and monitor • Interface with varying technologies • Store and access data in parallel • Metadata control (by “user”) • Contextual information (vs content) • Efficiently use indexes • Support compound keys

More Related