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Data classification
Identify important data and the controls it requires.
Discuss this capability ↗Protect sensitive data through access, policy, architecture and lifecycle controls.
Enterprise transformation rarely fails because a technology is unavailable. It stalls when architecture, operating context, data, security and adoption are treated as separate problems.
We bring those disciplines together so the capability can move from an initial priority into a repeatable operating model.
Enterprise technology creates momentum when architecture decisions are close to the work they are meant to improve.SOLVEXDATA / ENGINEERING PRINCIPLE
Define the business or technology behaviour that should improve.
Protect the constraints, controls and service expectations that matter.
Make ownership, observability and improvement part of the design.
We combine architecture decisions with engineering and operating context so the capability can move into production with clear ownership.
Identify important data and the controls it requires.
Discuss this capability ↗Align access with identity, role and business need.
Discuss this capability ↗Design protection for data at rest and in transit.
Discuss this capability ↗Connect data handling practices to defined privacy requirements.
Discuss this capability ↗Create evidence around access and important data activity.
Discuss this capability ↗Address retention, movement and disposal across the data lifecycle.
Discuss this capability ↗The outcome is a capability that is easier to operate, easier to evolve and better aligned to enterprise priorities.
Reduce unnecessary access and unmanaged data movement.
Make data ownership and access easier to understand.
Bring privacy considerations into architecture and workflows.
Create clearer evidence around important data activity.
We focus on the workloads, decisions and operating moments where the capability creates practical value.
Improve visibility and control around critical information.
Protect data used by reporting and analytical workloads.
Control how enterprise information enters intelligent applications.
Carry security and privacy controls into new platforms.
The delivery path is staged to reduce risk, create evidence early and leave behind a capability teams can run.
Identify critical datasets, flows, consumers and ownership.
Set access, protection, privacy and lifecycle expectations.
Implement controls across platforms and workflows.
Create monitoring and audit evidence.
Adjust controls as data use and architecture evolve.
Every enterprise environment is different. These are the conversations we typically bring into the room early.
Start with the data that is most sensitive, important or exposed, then align controls to risk and usage.
Yes. Classification, access, encryption, monitoring and lifecycle patterns can be designed across platform components.
Privacy requirements can be translated into data flows, access, retention and operational controls.
Let’s map the current state, target outcome and practical path forward with your team.