This lesson develops Parsing, Standardization, Validation, and Issue Classification within Oracle Enterprise Data Quality 12c: Profile, Audit, and Operate Ed 1.
The activity is anchored to a customer-data quality program measuring defects, standardizing records, identifying duplicates, and operationalizing controls, so each design, configuration, analysis, or support decision is tied to a realistic operating outcome.
The instructor will configure and verify processors, staged workflows, attributes, flags, and result views in the context of a customer-data quality program measuring defects, standardizing records, identifying duplicates, and operationalizing controls. The demonstration captures commands, configuration, transactions, output, logs, plans, or screenshots that prove both the intended behavior and the control boundary.
Learners complete a controlled exercise covering name, address, phone, email, and identifier parsing concepts and standardization, transformations, reference matching, and controlled correction, then introduce a realistic exception involving validation rules, issue codes, severity, exception samples, and acceptance thresholds. They record assumptions, exact steps, expected and observed results, a reversible correction, and the evidence required for operational acceptance.
Acceptance for Parsing, Standardization, Validation, and Issue Classification requires the result to be reproducible, traceable to approved inputs, consistent with the relevant Oracle or platform behavior, and supported by checks for security, data integrity, reliability, performance, and recoverability.
When the result differs from expectation, learners isolate the smallest proven cause across processors, staged workflows, attributes, flags, and result views, name, address, phone, email, and identifier parsing concepts, standardization, transformations, reference matching, and controlled correction; they avoid speculative production changes, preserve evidence, apply the lowest-risk correction, rerun the test, and document prevention.
Complete and defend a validated result for Parsing, Standardization, Validation, and Issue Classification with a reusable implementation record or runbook.