1 / 15

Data Warehousing: A Definition

Data Warehousing: A Definition. “A data warehouse is a single integrated store of data which provides the infrastructural basis for informational applications in the enterprise” Kelly, “Data Warehousing”, p55 Will be a collection of tools - not just a database

jarrod-bennett
Télécharger la présentation

Data Warehousing: A Definition

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. Data Warehousing: A Definition • “A data warehouse is a single integrated store of data which provides the infrastructural basis for informational applications in the enterprise” Kelly, “Data Warehousing”, p55 • Will be a collection of tools - not just a database • query system to support decision making • Ability to trawl (mine) in a way that suits the user • integrated store of consistent, up to date data • Main aim to maximise the effective use of data within a business. • Create a bridge between disparate systems

  2. Old Rationale for IS • Automate the business process • reduce costs • Information seen as a fortuitous by-product • Emphasis on IS as a input/processing/output • define functions • specify what system does • difficult to change outputs

  3. Problems With a Data Processing Approach • Data problems • resident in different systems • inconsistent • different attributes • different time bands/frames • irreconcilable • Deletion vs. archiving of data • inappropriate and inconsistent data models

  4. Issues in Moving to Data Warehousing Philosophy • Ownership issues • Planning across department/functional areas • Economic issues • Standardisation of data model • similar data entities in multiple systems • data inextricably bound with application • Standards in application design • piecemeal approaches to system implementation • Multiple interpretations of reality

  5. The Business Case for Data Warehousing • Reduce costs (?) • Increase business e.g. through better understanding of customers • Develop competitive advantage • Change the nature of the business

  6. Advantages of Data Warehousing • Removes query and reporting load from TPS • Allows more appropriate technology for queries and reports • Provides a more simple query interface to users • May provide a higher integrity DB than a TPS • Easy way of reporting across multiple systems • May provide a DB with a longer memory than a TPS! • May make TPS more secure by reducing access

  7. Disadvantages of Data Warehousing • May rely too heavily on data generated only from TPS • May complicate business processes by “institutionalising” reports, data for data’s sake • Learning curve too long - technical and business aspects • Culture of developing quick and dirty strategic applications • End-users may not have skills for building queries • Availability of data warehousing skills • Data warehouses require high maintenance • Cost of information may outweigh its benefit

  8. Problems to Consider • Extracting, cleaning and loading of data may be time consuming • Undetected error in systems feeding the warehouse • Warehouse project may highlight unrecorded data in existing systems • End user training in query and reporting tools may increase requests for IS written reports • End user approaches to calculations may differ due to different business views • Creation of a large-scale data warehouse may homogenise data - reducing content • Conflict between “need to know” and “right to know” mindsets

  9. Data Warehousing Tools • Meta-data modelling • Data transformation • Extract • Cleanse • Load • Database (relational, parallel) • Query language

  10. User Application Information Retrieval Application Application Importing Process Data Warehouse Periodic transformation And integration process TPS 1 TPS 2 TPS 3 Relationship Between Data Warehouse and Other Systems

  11. Some Political Issues (IS) • Who should a data warehousing development group report to? • Who should administrate over the warehouse? (DBS or development group) • How should the support of feeder system developers be gained? What about errors in the feeder system? • Who has responsibility for data quality monitoring? • What about changes to the feeder systems?

  12. Some Political Issues (User-IS) • Why should users give up control of user managed databases? • How is the co-operation gained of a user who’s spreadsheet is being automated? • Should design be for the needs of the masses or the most demanding users? • How many data marts should there be?

  13. Some Political Issues (User-User) • Who has access to what data? • Do all users define and interpret data the same way? • Who has the final say about the “correctness” of data

  14. General Political Issues • Imposes new obligations whose responsibilities are unclear. • May require a change in processes that an organisation may not be comfortable with. • Requires agreement on some and not all definitions of data

  15. Some Useful References... • Http://pwp.starnetinc.com/larryg • Kelly, (1998) “Data Warehousing”, Wiley

More Related