Data Architecture & Governance
We design data platforms with security, ownership, and access control built in from the start, so your teams trust the data and your auditors can verify it. Good data architecture is what makes everything downstream dependable, from executive dashboards to the AI agents that query on your behalf.
The problems this solves
Ownership is unclear
Nobody can say who owns a dataset, so quality issues bounce between teams instead of getting fixed.
Access is all or nothing
People either see everything or file a ticket and wait. Neither scales, and neither passes an audit.
Definitions drift
Finance and sales report different numbers for the same metric, and every meeting starts with reconciliation.
The stakes just went up
A SOC 2 push, a new regulation, or an AI initiative is exposing gaps you have been deferring.
Architecture and governance are one decision, not two
We design the zones your data moves through and the controls that travel with it. A policy set once applies everywhere, including to queries an AI agent writes on a user’s behalf.
Diagram of a governed data architecture: source systems flow into a raw landing zone, then modeled and tested data, then consumption by BI, AI, and applications. A governance layer spanning all zones enforces role-based access, row and column policies, ownership, and audit trail.
What a data architecture engagement includes
Scope flexes to where you are, from a greenfield platform design to a governance retrofit on an architecture that grew faster than its rules.
- Cloud data platform architecture and reference designs
- Role-based access control (RBAC) designed around how your teams actually work
- Row access and column masking policies for sensitive and regulated data
- Data ownership and stewardship models your organization will actually follow
- Environment strategy, naming standards, and promotion paths
- Metric and semantic definitions governed in one place, not four
- Lineage, audit readiness, and access review support
- Cost governance with guardrails on compute and storage spend
How we work
Assess
Map the current state honestly: where data lives, who can touch it, and where the risks actually are.
Design
Target architecture, access model, and ownership, documented in plain language your whole team can read.
Implement
Controls built into the platform itself, not bolted on around it, introduced domain by domain.
Operate
Access reviews, monitoring, and evolution as the organization changes, with us or with your team.
Outcomes
Access questions get answered in minutes, not meetings. And when the auditor asks who can see what, the answer is a query, not a scramble.
Frequently asked questions
Do we need a governance program before starting analytics or AI?
No. Governance should grow with the platform rather than precede it. We scope controls to the domains actually in use, then expand. AI does raise the stakes, though: agents inherit whatever permissions exist, so loose access becomes visible fast.
We handle sensitive data and are working toward SOC 2. Can you design for that?
Yes. We design platforms to be auditable by default: role-based access, masking on sensitive columns, and complete query logging. We work alongside your security team and your auditors rather than around them.
Is this Snowflake-specific?
No. We are a Snowflake Select Partner and much of our work lands there, but the architecture and governance patterns apply across modern cloud data platforms, and we support clients on other stacks.
How disruptive is a governance retrofit?
Less than the alternative. We introduce policies domain by domain with a validation window, so nothing locks down overnight. The goal is that most users never notice the change, except that the numbers start agreeing.
Where this connects
Data Engineering
We build the data pipelines and models everything else depends on: automated ingestion, a governed cloud warehouse, and version-controlled transformations with tests.
Data Migrations
We move data platforms and analytics workloads to modern cloud environments with minimal downtime, validated results, and careful coordination across every team downstream.
Analytics & Agentic Activation
Dashboards your teams check daily, and AI agents they can question in plain language, both reading from the same governed definitions.
Build on architecture that holds
Whether you are designing a new platform or bringing order to one that grew fast, we will meet you where you are.
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