Data Governance. One source of truth for management, marketing and IT - instead of five conflicting reports.

Data Governance Consulting and implementation

I help organize your data so the whole company works from a single source of truth

Marketing reports different conversions than sales. BigQuery has three definitions of an "active customer". Nobody knows which system is the source of truth for products or clients. Data Governance is not a "year-long IT project" - it's organizing roles, policies and processes so data is accurate, consistent, secure and usable. I implement this step by step, in the context of your analytics stack (GA4, BigQuery, Power BI, CRM) - not as a theoretical framework from a textbook.

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Does this sound familiar?

Different numbers in GA4, CRM and Excel

No single source of truth - every team builds its own version of the report.

Everyone has their own metric dictionary

"Conversion" and "active customer" mean different things in marketing, sales and finance.

GDPR - do we know where personal data lives?

Missing data classification, lineage and retention procedures make audits and compliance harder.

Duplicate customers across systems

CRM, ERP and the shop use different identifiers - no MDM or ID mapping.

New dashboard every quarter, zero trust

Shadow analytics - teams don't trust official reports and build their own spreadsheets.

AI/ML "doesn't work"

Garbage in, garbage out - models need clean data at the source.

How we work together - 4 steps

  1. 01

    Assessment

    Map of data systems, gaps and priorities. Identification of quick wins and high-risk areas.

    Deliverable: AS-IS report + risk heatmap
  2. 02

    Strategy

    Definition of roles (data owner, data steward), quality policies, classification and access. Workshops with business and IT.

    Deliverable: Data Governance Charter
  3. 03

    Implementation

    Data catalog, naming conventions, access rules, identifier mapping. Quick wins in the first 90 days.

    Deliverable: policies + templates + quick wins
  4. 04

    Maintenance

    Data quality monitoring, quarterly reviews, framework evolution aligned with business needs.

    Deliverable: quality KPIs + roadmap

Offer - what you get

Policies and standards

Naming conventions, data classification, retention, validation rules - documented principles your team actually follows.

Naming conventions Retention Classification

Data quality

Profiling, deduplication, quality KPIs: completeness, timeliness, consistency and accuracy.

Profiling Deduplication Quality scoring

Metadata and catalog

Business glossary, data catalog, lineage - you know where a metric comes from and who owns it.

Data Catalog Lineage Glossary

Master Data (MDM)

Golden record for customers and products, EAN/SKU/ERP code mapping across systems.

Golden Record ID mapping MDM

Security and GDPR

RBAC, data masking, consent management, audit procedures - compliance in practice.

RBAC Masking GDPR

Analytics integration

GA4 → BigQuery → Power BI on a single metric definition. Consistent reporting across teams.

GA4 BigQuery Power BI
  • Who it's for: ecommerce and retail (multiple ID systems), companies after GA4/BigQuery migration, organizations before AI/ML rollout, teams under GDPR pressure.
  • Model: assessment (1–2 weeks) → strategy (workshops) → quick win implementation → optional ongoing support (analytics retainer).
  • Outcome: one KPI definition, fewer Excel shadow reports, faster GDPR audits, readiness for AI and automation.

Free tools - start on your own

Before booking a consultation, you can assess your Data Governance maturity or deepen your knowledge.

Data Governance Checklist

Assess maturity in 5 minutes - 30 checkpoints in 6 categories with scoring and recommendations.

Run the checklist

Data Governance Guide

What DG is, key components, implementation framework and data steward roles - a complete guide.

Read the guide

Data Governance FAQ

EAN, SKU, GTIN, golden records and MDM - answers on product identifiers and data quality in practice.

Read FAQ
Krzysztof Surowiecki

Krzysztof Surowiecki. I help companies set up analytics so that management, marketing and sales work from a single source of truth - from product identifier mapping (EAN, SKU, ERP codes) through metric definitions in GA4 and BigQuery to access policies and data retention.

  • Hands-on experience with GA4, BigQuery, Power BI - not just slides, but real implementations.
  • Business ↔ IT bridge - I translate GDPR requirements into concrete rules in systems and processes.
  • NDA and work with sensitive data - standard on every project.

Trust - why clients choose me for analytics

20+years experience
150+projects
50+clients
7expert tools
  • Single point of contact: I don't hand off your project between teams - you work directly with me.
  • Consulting approach: diagnosis and quick wins first, then implementation with measurable business impact.
  • Confidentiality and security: NDA and working standards suited to data-sensitive organizations.

Contact - let's take the first step

Tell me where report conflicts come from and which systems need to speak the same language. In a consultation you'll get a priority map, scope proposal and indicative pricing.

  • Discussion of data systems, report conflicts and business goals.
  • Priority map: quick wins vs long-term actions.
  • Scope proposal (assessment / strategy / implementation) and pricing.
Book a consultation Take the checklist first