Spotify Data Governance Pilot Plan¶

Aligning Data Strategy with Business Growth, Compliance, and Innovation

Objective¶

This pilot establishes Spotify's Data Governance Framework within a controlled scope, identifying challenges, refining processes, and preparing for enterprise-wide scaling. The focus is on proving the framework's effectiveness in improving data quality, architecture, compliance, and cross-team collaboration before full deployment.

Scope¶

The pilot will be deployed in the Marketing department, focused on user engagement data:

User behavior logs;
Campaign performance metrics;
Personalization data.

Pilot Phases & Timeline¶

Phase	Duration	Key Activities	Success Metrics
1. Foundations	Months 0–3	Draft Spotify's Data Governance Policy (aligned with global standards)	Policy approved by CDO and Legal team
		Assign CDO and Data Stewards; formalize the Data Governance Committee (Legal, Engineering, Marketing, Product)	Committee chartered; roles documented in Collibra
		Pilot kickoff: test framework with Marketing (focus: user data for targeted campaigns)	Pilot scope and KPIs defined
2. Rollout	Months 3–12	Deploy Talend for automated validation of user engagement/recommendation data	95%+ of data meets quality standards
		Conduct GDPR/CCPA audit with VeraSafe; update privacy policies and consent flows	100% of DSARs answered within regulatory deadlines
		Launch role-specific training (CDO, Data Stewards, Marketing teams)	90% of pilot team completes training
3. Scale & Optimize	Months 12+	Monitor KPIs (data quality, DSAR response time, user trust metrics)	KPIs meet or exceed targets
		Expand framework to new regions/products (e.g., Podcasting, Ads)	Adopted by 2+ new departments
		Embed governance in AI/ML initiatives (e.g., bias mitigation for recommendations)	AI models audited for compliance and bias

Tools referenced: Collibra (data governance/cataloging platform), Talend (ETL), VeraSafe (privacy/compliance audits), Splunk (security monitoring).

Team Roles & Responsibilities (Pilot-Specific)¶

Team Member	Role	Pilot Responsibility
Robert CDO Jr.	CDO	Approve governance policy; sponsor the pilot at leadership level
Andrew Fiable	Data Steward (Quality)	Own data quality baseline and Talend validation workflows for Marketing data
François Kompliant	DPO	Lead GDPR/CCPA audit with VeraSafe; own DSAR/consent workflows
Vladislav DevOps	Engineering Lead	Integrate Collibra, Talend, Splunk, VeraSafe into pilot infrastructure
Paulo Tchacho	Marketing Director	Ensure campaign data usage aligns with governance policy during pilot
Emilio Taquet	Pilot Lead / Project Manager	Coordinate timeline, milestones, cross-team collaboration; track and report KPIs

(Full role definitions are in the Roles & Responsibilities section of the main framework - this table only maps pilot-specific ownership.)

Deliverables¶

Data Quality & Governance¶

Documented rules/procedures for data accuracy and consistency (stored in Collibra)
Centralized data environment for Marketing engagement data (Talend + Collibra)
Automated validation workflows for critical data (Talend)

Collaboration & Integration¶

Secure APIs for safe cross-team data sharing (e.g., Marketing Product)
Collaboration plan to break silos: cross-team workshops, shared dashboards in Collibra
Document data lineage in Collibra

Privacy & Trust¶

Privacy policy documentation aligned with VeraSafe audit standards
Transparency reports on data usage (e.g., annual compliance report)

Security, Ethics & Compliance¶

Data mapping by region and applicable regulation (VeraSafe)
Automated workflows for consent, DSARs, and incident reporting (VeraSafe + Splunk)
Bias-prevention controls and unauthorized-access alerts (Splunk)

Scalability¶

Cloud-based, scalable data architecture (Talend)
Third-party data partnership audit reports
Real-time dashboards for marketing/product decisions (Tableau + Collibra)

Timeline & Milestones¶

Milestone	Target Date	Responsible	Success Criteria
Kick-off Meeting	01/04/2026	Project Manager	Pilot scope, team, and KPIs finalized.
Data Assessment & Cleansing	01/06/2026	Data Steward (Andrew)	Initial data quality baseline established; Talend workflows deployed.
GDPR/CCPA Compliance Audit	01/12/2026	DPO (François)	Audit report completed; VeraSafe workflows for DSARs/consent implemented.
Technical Setup & Integration	01/03/2027	Engineering Lead (Vlad)	Collibra, Talend, Splunk, and VeraSafe integrated; APIs for data sharing deployed.
Mid-Project Review	01/04/2027	Project Manager	KPIs reviewed; adjustments made to processes/tools.
Final Review & Pilot Closure	01/06/2027	Project Manager	Pilot report delivered; framework approved for scaling.

Metrics¶

KPI	Description	Target
Data Quality Score	% of data meeting accuracy, completeness, and consistency standards.	95%+ data accuracy, ≤5% missing.
Compliance Score	% of data processing activities compliant with GDPR, CCPA, etc.	100% user consent obtained.
Data Access Speed	Time reduction for authorized users to access data.	20% faster access.
Silo Reduction	% reduction in data silos between departments (Marketing, Product, Data Science).	30% fewer silos.
Bias Detection Rate	% of critical AI models audited for bias and % bias reduction acheved.	100% audited, 50% bias reduction.
DSAR Response Time	Average time to respond to Data Subject Access Requests (DSAR).	40% reduction (e.g., 10 to 6 days).
Transparency Rate	% of users/teams understanding data usage practices.	90% comprehension.
Audit Efficiency	% of third-party data audits completed on time with no major non-compliance.	100% on-time, 0 major issues.

Training & Change Management¶

Hands-on workshops (Marketing + relevant teams) To ensure smooth adoption of the Data Governance Framework : governance processes (metadata management, data validation), tool training (Collibra, Talend, Splunk, VeraSafe), and data quality/security/compliance best practices.

1.5-2 hour sessions, in-person or virtual.

Role-specific training:

Data Stewards: data quality management and audits
Marketing leads: compliant data usage for campaigns
Technical teams: secure API integration and automation

Support resources:

Centralized documentation: user guide, quick-reference sheets (e.g., reporting non-compliance, accessing data), live FAQ (Confluence/Notion)
Short video tutorials (5-10 min) and monthly webinars
Dedicated helpdesk: standard requests <24h, urgent security issues <4h (Email or ticketing system.)

Feedback mechanisms:

Post-training satisfaction surveys (e.g., tool clarity, anticipated obstacles)
Biweekly meetings with Data Stewards and team leads
Anonymous suggestion box
Continuous improvement: e.g., if 60%+ report difficulty with a tool, schedule a targeted refresher

Evaluation and Lessons Learned¶

Objective: assess pilot success, document insights, and refine the framework before full-scale implementation.

Measure results against pre-defined KPIs (data quality, compliance, silo reduction)
Collect quantitative evidence of improvement (e.g., % reduction in missing data, DSAR response time)
Document successes, challenges, and unexpected outcomes, with actionable recommendations
Gather stakeholder and end-user feedback to refine the framework before scaling

Next Steps¶

Immediate (pilot launch):

Finalize pilot scope: confirm data types, teams, tools (Collibra, Talend, etc.)
Assign clear deliverable owners (e.g., Andrew for data quality, François for compliance)
Kick off with a cross-team workshop to align on goals and processes
Monitor and iterate using Splunk dashboards to track KPIs

Post-pilot (scaling):

Develop a roadmap to expand the framework to additional departments (Product, Ads), prioritized by impact and readiness
Update the Data Governance Policy based on pilot results and stakeholder feedback, addressing any gaps or inefficiencies identified

Prepared by Frederic LAGNIEZ | 10/07/2026 | Project Manager | Pilot report delivered; framework approved for scaling.