Published: 13 February 2023
Summary
D&A technical professionals typically create cascading, complex ETL scripts to get the right data at the right quality to the right people at the right time. Edith Cowan University minimized its data management resourcing by 90% using metadata-driven patterns to generate and manage ETL scripts.
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Overview
Key Findings
Managing ETL scripts individually results in resource-intense data management practices because every change to business logic or technology requires relevant scripts to be updated accordingly.
ETL scripts can be organized into a small set of types based on their functionality or process logic; each set has a predictable and manageable number of variants.
Writing ETL scripts according to their function or process logic enables liberal reuse of existing scripts with similar functionality.
Managing ETL scripts based on their function or process logic also minimizes ongoing data management work because an update to a particular script can be cascaded to dozens or
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