Unified Semantic Data Modeling
Eliminate discrepancies and deliver accurate, trusted insights organization-wide.
Consistency Across the Organization: Define metrics, dimensions, and relationships once for consistent KPIs across tools.
Model Once: Reduce ETL overhead and enable real-time analytics with trusted, reusable models.
Never Move Your Data: Virtualize data in place without movement using query pushdown to platforms like Snowflake, BigQuery, and Databricks.
Semantic Modeling Language: Centralize metric definitions using an open-source, YAML-based Semantic Modeling Language (SML) that supports version control and CI/CD integration.
Universal Semantic Hub: Integrate models from dbt, Power BI, LookML, and more under a single governance framework.
Business Context for Text-to-SQL Gen AI
Enhance AI precision and make analytics accessible to all users with a universal semantic layer.
Contextual AI: Embed business context into generative AI models to prevent hallucinations.
Accurate NLQ: Enable accurate natural language queries (NLQ) without requiring technical expertise.
AI Accessibility: Democratize access to AI-powered analytics with trusted semantic intelligence.
Performance Optimization
Faster insights with reduced data engineering overhead and lower costs powered by a universal semantic layer.
Optimized Performance with Real-Time Analytics: Access live data directly from sources using advanced query pushdown and data virtualization, eliminating the need for data movement, ETL or duplication.
Accelerated Insights with Smart Automation: Automate query optimization, aggregate generation, and caching to reduce latency, lower cloud costs, and deliver rapid results.
Scalable and Modern Workflows: Scale seamlessly for complex workloads and large datasets with AtScale’s next-generation OLAP engine, enabling multidimensional analysis on cloud data platforms while modernizing traditional SSAS workflows.
Streamlined Governance
A universal semantic layer offers secure, compliant data access while enabling decentralized innovation.
Data Security: Build trust in your data with enterprise-grade security and governance.
Access Control: Enforce granular, role-based access control to protect sensitive data.
Centralized Governance: Govern metrics, dimensions, and query performance from a central platform.
Tool Integrations: Integrate with tools like Alation and Collibra for enhanced data discoverability and literacy.
Seamless Connectivity: Seamlessly connect with data catalogs like Alation and Collibra, identity management systems like Keycloak, and observability tools via OpenTelemetry.
Multi-Persona Modeling
Foster collaboration and ensure flexibility for diverse users.
Team Collaboration: Empower business analysts, data engineers, and data scientists to collaborate seamlessly.
Flexible Modeling: Support code-first (YAML-based SML) and no-code (drag-and-drop) modeling.
CI/CD Integration: Manage semantic models with CI/CD workflows via Git integration.
Time-Saving One-Click Modeling: Leverage AI to automate semantic modeling to reduce manual effort, ensure accuracy, and speed up decision-making.
Version Control: Integration with Git for streamlined version control and deployment.
Flexible Deployment & Pricing Options
Operational flexibility for modern enterprise environments.
Flexible Deployment: Deploy the universal semantic layer in public cloud, private cloud, or on-premises with Kubernetes.
CI/CD Integration: Integrate seamlessly with CI/CD pipelines for automated deployments.
Containerized Deployment: Deploy in under 5 minutes using Kubernetes or Docker.
Marketplace Availability: Native Application in Snowflake Marketplace or Kubernetes App on Google Cloud Marketplace
Simple Consumption-Based Pricing: Optimize costs with pay-as-you-go pricing, with no fees for data size, users, or queries.
