An ETL Metadata Model for Data Warehousing

Meta-data is essential for understanding information stored in data warehouses. It helps increase levels of adoption and usage of data warehouse data by knowledge workers and decision makers. A meta-data model is important to the implementation of a data warehouse; the lack of a meta-data model can...

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Bibliographic Details
Published inJournal of computing and information technology Vol. 20; no. 2; pp. 95 - 111
Main Authors Rahman, Nayem, Marz, Jessica, Akhter, Shameem
Format Journal Article Paper
LanguageEnglish
Published Sveuciliste U Zagrebu 2012
Fakultet elektrotehnike i računarstva Sveučilišta u Zagrebu
Subjects
Consumption
data warehouse
Data warehouses
Data warehousing
Decision making
EDW
ETL metadata
Mathematical models
Metadata
metadata model
Methods
Monitoring
observation timestamp
Online AccessGet full text
ISSN1330-1136
1846-3908
DOI10.2498/cit.1002046

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Summary:Meta-data is essential for understanding information stored in data warehouses. It helps increase levels of adoption and usage of data warehouse data by knowledge workers and decision makers. A meta-data model is important to the implementation of a data warehouse; the lack of a meta-data model can lead to quality concerns about the data warehouse. A highly successful data warehouse implementation depends on consistent meta-data. This article proposes adoption of an ETL (extract-transform-load) meta-data model for the data warehouse that makes subject area refreshes meta-data-driven, loads observation time-stamps and other useful parameters, and minimizes consumption of database systems resources. The ETL meta-data model provides developers with a set of ETL development tools and delivers a user-friendly batch cycle refresh monitoring tool for the production support team.
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85081
ISSN:1330-1136
1846-3908
DOI:10.2498/cit.1002046