Solutions · Data management
Data Governance
Governance defines who may take what action, on which data, in what circumstances. We build a framework that fits your organisation instead of forcing you into someone else's.
What we do
- Review how data is handled across systems, processes and teams
- Set ownership, policies, standards and decision rights
- Establish metadata, lineage, documentation and quality measures
- Embed governance into change and business-as-usual processes
Outcomes
- Named owners and clear accountability for critical data
- Less friction for the people who need data to do their jobs
- Evidence of control for auditors and regulators
- A foundation the AI governance capabilities build on
What governance actually decides
Good data governance defines the procedures and responsibilities for the quality and security of the data an organisation uses. More precisely, it establishes who has the authority to take what action, on what data, under which circumstances, and by what method.
It supports the wider data management strategy rather than standing apart from it, and it works best when it takes as little friction out of people’s day as possible.
Four questions we start with
- Access. Are users and business applications slowed by friction when they need data?
- Usability. Is the data well organised and documented, for people and for the tools that consume it?
- Integrity. Is there fundamental integrity across all of it, in use and at rest?
- Security. Are the right policies and tools in place to protect your data and your customers’ data?
The answers usually point at the same few causes: unclear ownership, undocumented definitions, and controls that exist on paper but not in the flow of work.
What we build
Our framework adapts to your architecture, structure, metadata, storage and movement, interoperability, documentation, uniqueness, quality and security. We make recommendations across strategy, structure, policies and standards, people, process and systems, and we look for quick wins early, because a governance programme that shows nothing for a year loses its sponsors.
- Ownership and decision rights for critical data
- Policies and standards written to be followed, not filed
- Metadata, lineage and documentation that make data findable
- Quality measures and the reporting that keeps them honest
- Governance embedded into change and business-as-usual processes
What it changes
Correct and efficient management of data improves the accuracy of data capture, raises operational efficiency, supports better decisions, and reduces regulatory and security risk. It is also the foundation the AI capabilities depend on: an AI system can only be governed if the data feeding it already is.
Common questions
How do I build the data disciplines my business goals depend on?
We have the skills, experience and people to help you create the teams and implement the technology to reach those goals. If you would rather focus on your core business, we can put tailored solutions in place that maintain the capability for you.
Ready to move AI into production with proof?
Leave your details and we will arrange a conversation.