/case-studies/data-qa-integrity-pipeline-salesforce/
growthCurve
Salesforce (Salesforce.org)

Data QA & Integrity Pipeline

Built a rigorous data QA and validation pipeline connecting Oracle, Business Objects, and Salesforce CRM to ensure reporting accuracy for global GTM teams.

Public Sector & Education2021Data GovernanceData QABI
Context

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.

Approach

The Route Map

Step-by-step path from challenge to outcome.

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.

Execution

The Stack

Channels, tools, and MarTech used to deliver results.

Channels

  • Data Governance
  • Data QA
  • BI

Tools

  • HubSpot
  • Salesforce
  • Looker

MarTech

  • Attribution
  • Analytics
  • Automation
Results

Outcomes Delivered

85%

Data Quality

Improved

Dramatically reduced

Reporting Errors

Accuracy

190%

Update Cycles

Accelerated

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

Improved data quality by ~85%

Reduced reporting errors dramatically

Accelerated update cycles by 190%

Lessons

What's Next

Key takeaways and ongoing opportunities.

This engagement demonstrates the power of a systematic, data-driven approach to GTM. The results speak to the importance of clear strategy, proper execution infrastructure, and continuous optimization. Moving forward, the focus shifts to scaling these wins and identifying the next growth lever.

Ongoing Optimization

Continuous monitoring and refinement to maintain momentum and identify new opportunities.

Scale & Expand

Apply proven frameworks to adjacent markets, channels, or product lines.

Ready for results like these?

Let's discuss how I can help accelerate your growth.