Streamline Enterprise Data Governance with a Semantic Layer
Consistent Policies
Ensure consistent governance policies across tools and teams.
Data Security
Protect critical data assets with granular access controls.
Simplified Pipelines
Eliminate manual governance overhead with automated data governance features.
Empowered Innovation
Create and customize data products without IT dependency.
Governed Insights
Access metrics and dimensions that are secure, consistent, and trusted.
Accelerated Development
Use pre-built components to speed up data product creation.
Collaboration & Compliance
Solutions that drive innovation while maintaining governance and compliance.
Faster Insights
Streamline analytics pipelines for real-time data access and faster decision-making.
Data Trust
Build organizational trust with consistent, governed data.
Govern at Scale Without Slowing Down Your Data Teams
Unified Policy Enforcement: Govern metrics, definitions, cloud resource consumption, and query performance from a single platform while enabling decentralized data product creation.
Composable Analytics Building Blocks: Manage reusable components like pre-built models, metrics calculations, and conformed dimensions.
Semantic Model for All Users: Combine code-first modeling for engineers with a visual canvas for business analysts.
Secure Every Query Without Blocking Access or Speed
Granular Row and Column-Level Security: Enforce detailed access controls to safeguard sensitive data.
Seamless Authentication: Integrate with existing credentials and BI tools for secure access.
Dynamic Policy Enforcement: Ensure real-time compliance without interrupting workflows.
Balance Innovation and Governance with a Federated Semantic Layer
Hub and Spoke Innovation: Allow teams to create their own data products based on centrally governed models.
Shared Semantic Objects: Reduce redundancy and promote collaboration by sharing reusable models, metrics, and dimensions.
Centralized Hub: Maintain a single source of truth for core governance standards.
Connect Your Entire Data Stack — Without Breaking Your Workflows
Metadata Management: Open integration with data catalogs like Alation and Collibra ensures governed data is discoverable.
Semantic Language Support: Bridge semantic languages like dbt, Power BI, and LookML for universal metrics alignment.
No Data Movement: Query data in place to ensure scalability and minimize disruptions.
Frequently Asked Questions
How does AtScale support data and analytics governance?
AtScale enforces centralized governance through its semantic layer, enabling consistent business logic, access controls, and metric definitions across all tools and users—including AI agents. This ensures both human and autonomous consumers interact with data under the same rules and oversight.
Does AtScale control who can see and access data?
Yes. AtScale applies your existing data access policies—including role-based access control (RBAC), row-level security, and column masking—to every query, whether it comes from a dashboard, an analyst, or an LLM-powered agent. All data access is secure, controlled, and compliant.
Can AtScale help prevent inconsistent reporting?
Absolutely. AtScale creates a shared semantic layer that acts as a single source of truth for all tools and users. Whether insights are surfaced in Excel, Tableau, Python, or via a generative AI assistant, everyone (and every agent) works from the same, consistent definitions.
How does AtScale handle data security?
AtScale never stores or moves your data. It queries data in place and inherits the security protocols of your data warehouse. This design ensures a secure, compliant environment for both BI tools and AI systems querying sensitive information.
Does AtScale support auditability and data lineage?
Yes. AtScale offers full visibility into how metrics are defined, where they’re used, and who—or what—is accessing them. This includes traceability for AI agents, enabling transparent, auditable insights and clear data lineage across tools and workflows.
Can I apply governance policies across multiple BI tools?
Yes. AtScale enables cross-platform governance through a centralized semantic layer, eliminating the need to manually replicate rules in each BI tool. This also ensures that any AI agent accessing data through different interfaces adheres to the same governance policies.
Is AtScale compliant with industry standards and regulations?
AtScale is built to meet enterprise-grade compliance needs—including HIPAA, SOC 2, GDPR, and more—based on your deployment model. Its support for agentic AI is fully aligned with these standards, ensuring secure and compliant AI adoption.
How does AtScale balance governance with self-service analytics?
AtScale enables governed self-service by giving business users and AI agents access to trusted, reusable data models—while IT retains full control over metric logic and access permissions. This structure reduces risk without slowing down insight generation or innovation.
How does AtScale handle governance for AI agents?
AtScale extends enterprise-grade governance to AI agents by enforcing the same access controls, metric definitions, and data policies used across BI and analytics. Whether an LLM, co-pilot, or autonomous agent is querying data, AtScale ensures it operates within defined guardrails—respecting role-based access, row-level security, and semantic consistency. This guarantees that AI agents retrieve only authorized data, generate explainable outputs, and contribute to compliant, trustworthy decision-making at scale.
