Is6120 owen devitt 100000523
This presentation is the property of its rightful owner.
Sponsored Links
1 / 13

IS6120 Owen Devitt 100000523 PowerPoint PPT Presentation

  • Uploaded on
  • Presentation posted in: General

IS6120 Owen Devitt 100000523. Data Warehouse (Corporate Information Factory) “You can catch all the minnows in the ocean and stack them together and they still do not make a whale.” Bill Inmon. Data Mart (Data Warehouse Bus)

Download Presentation

IS6120 Owen Devitt 100000523

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.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.

- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript

Is6120 owen devitt 100000523


Owen Devitt


Is6120 owen devitt 100000523

Data Warehouse

(Corporate Information Factory)

“You can catch all the minnows in the ocean and stack them together and they still do not make a whale.”

  • Bill Inmon

Data Mart

(Data Warehouse Bus)

“… The data warehouse is nothing more than the union of all the data marts …”

  • Ralph Kimball

Two types of data mart

Two Types of Data Mart

  • Dependent Marts

  • Independent Marts

Legacy Systems

Data warehouse

Data Warehouse

  • Top-Down approach

  • Holds multiple subject data

  • Services the needs of all users – owned by corporation

  • Low-level granularity

  • Normalized

  • Useful for data mining – discovering previously unknown connections

Data warehouse1

Data Warehouse

  • Criticism

  • Kimball and other data mart vendors suggest that DWs are large, long-term projects and that value is produced only after a number of years

    • Inmon refutes this claim (Inmon, 1999)

  • Expensive to maintain

  • Slow deployment

  • Data warehouse development

    Data Warehouse Development

    • Iterative development

    Data mart

    Data Mart

    • Bottom-up approach

    • Owned by a department

    • Services the needs of specific business units/departments

    • Star-join structure

    • Technology optimal for access and analysis

    • Rapid Deployment

    • “…departments and divisions are going to create their own mini data warehouses to answer urgent business questions…” (Kimball, 1998)

    Data mart1

    Data Mart

    • Criticism

    • Inmon suggests that data mart granularity is not as low-level as data warehouse granularity

      • Kimball refutes this claim (Kimball, 1998)

  • Large amounts of redundancy

  • High-level granularity (according to Inmon)

  • Synchronicity an issue

  • Large numbers of data marts become as difficult as legacy systems to integrate

  • Data mart development

    Data Mart Development

    • Independent development



    • Both use a staging area

      • Data Warehouse (DW view)

      • Backroom (DM view)

  • Both extract from a single source once

  • Both claim to be based on the most atomic data available from the source

  • Key differences

    Key Differences

    Data Warehouse

    • Hard work is done at the beginning

    • Dependent Data Marts – sourced from the DW

    • Iterative development

    Data Mart

    • Hard work is done on integration

    • Independent Data Marts – sourced from the legacy systems

    • Independent development



    • A Data Warehouse may be equal to the sum of its dependent Data Marts

    • Data Marts are useful for organizations that do not intend to utilize a corporate-wide data warehouse

    • Data Warehouse architecture is more robust and scalable than Data Mart architecture

    • Only the strictest, most forward-thinking data mart development can be equivalent to a data warehouse



  • Login