Data Quality & Governance
Ensure data is accurate, trusted, and governed across the organization.
Overview
Governance that actually works
Most data governance efforts fail not because of tools, but because they are disconnected from how the business operates. Data definitions are unclear, ownership is inconsistent, and quality issues surface too late. The result is data that exists, but cannot be trusted.
We take a different approach, focusing on governance as an operating model, not a tool. Using Snowflake Horizon, Alation, Atlan, and modern data practices, we define ownership, improve data quality, and embed governance into how teams work. The result is data that is accurate, trusted, and usable across the business.
Clear ownership and accountability
Define who owns data and how it is managed across the organization.
Improved data quality
Identify and resolve issues early through validation and monitoring.
Embedded governance
Integrate governance into workflows, not separate processes.
Benefits of our Approach & Outcomes
We focus on governance that enables the business. By defining clear ownership, standardizing data definitions, and improving data quality, we ensure teams can trust and use data with confidence. This reduces rework, improves alignment, and accelerates decision-making across the organization.
From data quality monitoring to governance frameworks, we design systems that scale across teams and use cases. The result is a consistent, trusted data foundation that supports analytics, AI, and operational workflows without constant validation.
From Policies to Adoption
Governance only works when it is adopted. We design governance models that align with how teams operate, ensuring policies are not just defined, but used. This includes embedding governance into tools, workflows, and day-to-day processes.
By combining technology with strong operating models, we help organizations move beyond documentation to real impact. The result is governance that improves data quality, builds trust, and supports long-term scalability across the business.
“Archetype has been a fantastic partner, helping us to focus our data governance approach on achieving real outcomes. They have helped us every step of the way, including managing the Data Governance Operations team as part of the implementation effort.”
Frequently Asked Questions
Answers to common questions about data quality and governance.
What is data governance?
Defining ownership, policies, and processes for managing data.
Why do governance programs fail?
Lack of alignment, ownership, and business adoption.
What tools do you use?
Snowflake Horizon, Alation, Atlan, and governance platforms.
How do you improve data quality?
Validation, monitoring, and clear ownership across data.
