THE CHALLENGES
No one owns the data
Clear roles and responsibilities are missing, so data quality issues keep coming back. Duplicate work becomes routine, costs grow and trust in data erodes.
Operating models do not stick
Policies and principles are written, but they are not part of everyday work. Rules that no one follows create a false sense of security.
AI raises the stakes
AI uses data at scale, so quality and access problems multiply. The EU AI Act sets requirements for data management that most organizations do not yet meet.
Control kills the speed
Governance gets built into heavy bureaucracy. Approvals and committees slow down development, so teams bypass the rules entirely.
Modern data governance is not about control. It makes using data safe and fast.
OUR PRINCIPLES
How we build data governance that works in daily operations.
Every Arked governance engagement is guided by clear principles. They ensure you get an operating model that lives in daily work. No documentation left in a binder.
01
Minimum structure, no bureaucracy
We build only the minimum structure needed. The goal is productized data that is safe and fast to use. The way of working earns its place by speeding up development.
02
Business owns data
Data owners sit in the business, not in IT. They decide which data matters most and what is required of the data. Collaboration requires clear roles and responsibilities.
03
Built for daily work
Roles, rules and quality practices live in everyday processes and tools, not in documents. That is the difference between governance on paper and governance that works.
04
Compliance as an outcome
When ownership, quality and controls work, GDPR and AI Act requirements are largely met as a by-product. Not as a separate project.
How we put data governance into practice.
Engagements range from a short assessment to ongoing governance leadership. Most clients start with a light current-state assessment and expand from there.
Choose the service that fits your situation
Current and target state assessment
2-3 weeks
We map the current and target state of your data: sources of business value, ownership, quality, roles and risks.
You get a gap analysis with root causes and prioritized recommendations.
Data operating model
2-4 weeks
A lightweight operating model sized for your organization: data ownership, roles and responsibilities, decision-making forums and a rollout plan. Built for you, not copied from a framework.
Operating model pilot
4-8 weeks
The operating model is piloted through a concrete data product and adapted to your organization. At the same time, ownership and practices are taken into the team’s daily work. You see the value in practice before scaling.
Ongoing support
As needed
We support the rollout by onboarding people, coordinating the work and helping develop the operating model further.
Interim governance lead
Ongoing, flexible
Senior-level governance leadership on a part-time basis. We drive the rollout, coach data owners and make sure the model sticks. Fixed monthly price, flexible commitment.
CLIENT FEEDBACK
A senior-level data and AI partner for demanding projects
9.8 / 10
Average client rating for delivered AI and data engagements.
REFERENCES
CASE Keva: AI-Ready Data Strategy and Data Governance Transformation
Building a stronger AI-ready data foundation: The challenge Keva has a long history of leveraging [...]
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Case HSL: AI and Data platform modernisation
Scattered data slowed development and was not AI-ready HSL’s data was scattered across multiple platforms [...]
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Flexible Architecture and Capability Design, Case Example: Keskisuomalainen
Today, many organizations struggle to turn their business vision and digital strategy into practical capability [...]
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