Semantic Hub

This is a new beta feature under development.

Important Disclaimer Some of the features detailed in this document may not apply and/or be available for the particular edition/version you are using.

Overview

• Vendor-neutral, metadata-only solution
• Implements performance and governance in the database
• Accessible to BI, AI, spreadsheets, and embedded apps via standard SQL. Generates BI semantic models for easy access and documentation
• Supports code-first, UI-first, and import-based model creation
• No runtime fees.

The Problem

• Data complexity is growing exponentially.
• Multiple BI tools and analytics platforms create metric inconsistencies.
• Generative AI (GenAI) needs trusted, contextual data to avoid hallucinations.
• Businesses struggle with governance, performance, and cost across diverse systems.

Objectives

• Enable a Business Analyst to translate raw data into business concepts, like metric, dimension, hierarchy, and standardize them in database semantic layers to make it available to:
• AI (Snowflake Cortex, Databricks Genie, etc.)
• BI (Power BI, Tableau, etc.)
• Spreadsheets (Excel, Google Sheets, etc.)
• SQL applications (embedded BI, etc.)
• Performance and Cost Optimization (database caching)
• Row and Column level Security
• CI/CD integration (GIT)

Key Benefits

• Standardization & Consistency – One definition of metrics everywhere.
• Accessibility – Intuitive business terms for all users.
• Governance & Security – Object and row-level security and compliance controls.
• Performance Optimization – DB-native aggregations and intelligent caching.
• No Vendor Lock-in – Avoids proprietary APIs and drivers.

Architecture