A Simplified Approach for Quality Management in Data Warehouse

TL;DR

This paper presents a metadata-based framework for managing and analyzing data quality in data warehouses, addressing prevalent quality issues to improve decision-making and reduce economic impacts.

Contribution

It introduces a simplified metadata-driven approach for assessing and managing data quality in data warehouses, enhancing existing quality management practices.

Findings

Effective metadata framework for quality analysis

Improved detection of data quality issues

Enhanced decision-making support

Abstract

Data warehousing is continuously gaining importance as organizations are realizing the benefits of decision oriented data bases. However, the stumbling block to this rapid development is data quality issues at various stages of data warehousing. Quality can be defined as a measure of excellence or a state free from defects. Users appreciate quality products and available literature suggests that many organization`s have significant data quality problems that have substantial social and economic impacts. A metadata based quality system is introduced to manage quality of data in data warehouse. The approach is used to analyze the quality of data warehouse system by checking the expected value of quality parameters with that of actual values. The proposed approach is supported with a metadata framework that can store additional information to analyze the quality parameters, whenever required.