Data Governance · case study

Data QA & Integrity Pipeline

Client: Salesforce (Salesforce.org)

Industry: Public Sector & Education

Year: 2021

Data Quality85%

Reporting Error ReductionDramatically reduced

Update Speed190%

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.

Our methodology

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.

Outcome instrumentation & delivery

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

Impact trajectoryKey metrics

“Established a durable data QA pipeline that ensured consistent, trusted reporting for global GTM teams”

Salesforce (Salesforce.org)

Outcome summary

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