Data Governance · case study
Data QA & Integrity Pipeline
The challenge
Data feeding the marketing and revenue dashboards was inconsistent and prone to quality issues. Reporting involved manual reconciliation across Oracle, BO, and CRM sources every week. Pipeline errors caused misalignment between Marketing, Sales, and Finance KPIs. Leadership lacked confidence in the accuracy of pipeline, contribution, and performance metrics. Data integrity checks were undocumented, unscalable, and reliant on individual knowledge.
How the work unfolded
1. Oracle SQL Validation: Built reusable SQL scripts for validating pipeline
Oracle SQL Validation: Built reusable SQL scripts for validating pipeline, stage progression, and campaign data
2. Business Objects QA Workflow: Standardized extraction and integrity checks before CRM ingestion
Business Objects QA Workflow: Standardized extraction and integrity checks before CRM ingestion
3. Data Reconciliation Framework: Mapped cross-system discrepancies and automated resolution steps
Data Reconciliation Framework: Mapped cross-system discrepancies and automated resolution steps
4. Documentation & Governance: Created repeatable procedures enabling operational continuity
Documentation & Governance: Created repeatable procedures enabling operational continuity
5. Integration Layer Hardening: Strengthened dependencies between CRM
Integration Layer Hardening: Strengthened dependencies between CRM, MAP, and BI pipelines.
The execution
Oracle SQL Validation: Built reusable SQL scripts for validating pipeline, stage progression, and campaign data. Business Objects QA Workflow: Standardized extraction and integrity checks before CRM ingestion. Data Reconciliation Framework: Mapped cross-system discrepancies and automated resolution steps. Documentation & Governance: Created repeatable procedures enabling operational continuity. Integration Layer Hardening: Strengthened dependencies between CRM, MAP, and BI pipelines.
The outcome
Measurable impact across pipeline, efficiency, and growth.
Established a durable data QA pipeline that ensured consistent, trusted reporting for global GTM teams
Improved data quality by ~85%
Reduced reporting errors dramatically
“Established a durable data QA pipeline that ensured consistent, trusted reporting for global GTM teams”
Salesforce (Salesforce.org)
Outcome summary
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Expertise applied: Marketing Analytics & Reporting
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GTM field notes
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