GDPR + AI Act ready
Personal data mapping, legal basis, retention, DPIA support and AI models in scope.
03 / DATA-GOVERNANCE
Big Data
Data GovernanceBig Data — Know what you have, where it lives, who uses it, and why.
Know what you have, where it lives, who uses it, and why.
Pragmatic data governance: catalog, lineage, ownership, quality, access, privacy. No red tape: simple rules, automation, clear accountability.
100%
Critical data products cataloged
−50%
Time to find data
GDPR
Documented compliance
§ A
Overview
Most data governance programmes fail through excess formalism. Our approach starts from value: we catalog critical data products first, define real owners, automate as much as possible (lineage, quality checks, access control) and only formalise where needed.
We align governance to regulatory requirements (GDPR, AI Act, NIS2, DORA, sectoral) without building a bureaucratic machine that slows the business down.
§ B
What's included
- Maturity assessment and operating-model definition
- Identification of data domains and data products
- Automated data catalog implementation (DataHub, Unity, Atlan)
- End-to-end lineage from source to BI
- Data quality SLA and monitoring
- Privacy by design and data classification
- Fine-grained access control (row/column level)
- Data literacy and community programme
§ C
Deliverables
What you get at the end — or along the way — of an engagement on Data Governance.
- D/01Operating model (RACI, processes, committees)
- D/02Catalog populated with technical and business metadata
- D/03Glossary and business definitions
- D/04Data quality dashboard
- D/05Access and retention policies
§ D
Use cases
Governed self-service analytics
Business users find certified data without asking IT.
Trust in the numbers
A single version of the truth for critical business metrics.
M&A integration
Mapping and harmonisation of acquired companies' data.
§ E
Our process
01
Assess
Maturity, regulatory gaps, business priorities.
02
Design
Operating model, tool choice, ownership.
03
Pilot
One end-to-end data domain as a blueprint.
04
Roll-out
Extension to the whole organisation with community and training.
05
Sustain
Adoption metrics, policy evolution, periodic audits.
§ F
Technologies
DataHub · Atlan · CollibraUnity Catalog · PolarisOpenMetadataGreat Expectations · SodaImmuta · PrivaceraBigID · OneTrust
Indicative stack. We adapt choices to your context, internal skills and existing constraints.
§ G
Frequently asked questions
Q/01Should I run a big initiative first or start small?+
Always start small from a high-value domain. Big-bang initiatives fail.
Q/02Do I need a Chief Data Officer?+
Not necessarily. You need clear ownership. We can cover the role on an interim basis while you build it internally.
Q/03How long before results?+
First certified data products and populated catalogs in 8–12 weeks. Full maturity in 12–18 months.
Next step
Let's talk about data governance.
A 30-minute call to understand your context and whether we can really help. No commitment.