Data you cannot trust
When the CFO and the COO present different revenue numbers at the same board meeting, you have a governance problem. Data quality issues are rarely technical — they are organizational. Multiple teams define "customer" differently, ETL jobs silently drop records, and nobody knows which dashboard shows the correct number.
Regulatory pressure makes this worse. GDPR, KVKK, BDSG and industry-specific regulations require knowing what data you have, where it lives, who has access and how long you keep it. Without governance, compliance is guesswork.
Assess & Define
We audit your data landscape, identify governance gaps and define data ownership, quality rules and policies aligned with your regulatory requirements.
Implement & Catalog
Data catalog deployment, quality rule automation, lineage tracking and access control implementation. Governance built into pipelines, not bolted on.
Operate & Comply
Ongoing governance operations: quality monitoring, policy enforcement, compliance reporting and data steward enablement.
What we deliver
Automated quality checks, profiling and cleansing across all data assets. Quality rules enforced at ingestion, transformation and consumption stages.
Searchable data catalogs with business glossaries, technical metadata and usage analytics. Every dataset documented, classified and discoverable.
End-to-end lineage tracking from source to report. When a number looks wrong, you can trace it back through every transformation to the original source.
Role-based access control, data classification and masking policies. Ensuring the right people see the right data — and nothing more.
GDPR, KVKK, BDSG and industry-specific compliance frameworks. Data retention policies, consent management and audit-ready documentation.
Data quality issues undermining trust in your reports?
Talk to a governance specialist who has built frameworks for regulated enterprises.
Top-5 Turkish Retail Bank
Inconsistent KPI definitions across 10+ departments. No data ownership, no lineage and regulatory compliance was unverifiable.
We defined data ownership roles, implemented a data catalog with business glossary, automated quality checks across all pipelines and established compliance reporting.
Unified KPI definitions across the organization. Data quality score improved from 72% to 96%. Audit-ready compliance documentation.
Where we apply it
- Ensure every department trusts the same data definitions
- Achieve GDPR/KVKK compliance with audit-ready documentation
- Eliminate duplicate and conflicting master data across systems
- Raise data quality scores from 70% to 96%+
- Let analysts find the right dataset in minutes, not days
Technologies
Microsoft