USE CASE: Hybrid Multi-cloud analytics
From Complex Infrastructure to Easy Data Consumption
Timbr transforms complex, hybrid, and multi-cloud architectures into a unified semantic layer that makes data easy to consume. Model once, and deliver consistent, governed access to metrics and concepts across all platforms, so business users, analysts, and AI can query and explore distributed data using familiar, SQL-based semantics.
BEHIND THE USE CASE
Timbr enables the Semantic Data Fabric aimed to connect diverse, distributed data sources by means of a virtual, unified semantic data model mapped to federated data, without the need for data duplication or complex ETL (Extract, Transform, Load) processes.
REFERENCE ARCHITECTURES
Timbr embedds semantic intelligence into leading architectures including, Microsoft Fabric, Google Cloud, AWS Cloud and Snowflake.
Key Capabilities
Unified Semantic Modeling Across Sources
Timbr lets you create a single ontology that spans data in Databricks, Snowflake, BigQuery, Synapse, AWS, and on-premises systems. Model relationships, business rules, hierarchies, and classifications across all environments using one SQL-based semantic layer.
- Logical models span clouds and on-prem systems.
- Relationships and metrics are defined once and reused everywhere.
- Data stays where it is—no replication required.
Virtualized Querying and Federated Access
Timbr’s virtualization engine allows seamless querying across distributed data sources. Users write standard SQL against the ontology, while Timbr handles query federation and optimization.
- Query data without knowing its physical location.
- Avoid complex data movement or consolidation.
- Maintain performance with pushdown optimization and intelligent joins.
Consistent, Governed Metrics Everywhere
Define governed, reusable metrics in one place and expose them to all users and tools. Timbr’s semantic metric store ensures consistency and reduces duplication across reporting and analytics.
- Centralized metric logic with cross-cloud visibility.
- Business teams consume metrics via BI tools, SQL, or APIs.
- Integrates with native catalogs like Unity Catalog and Purview.
Business Benefits
Accelerated Analytics Delivery
Deliver faster insights across distributed data without waiting for centralization or reengineering.
Reduced Data Movement Costs
Eliminate unnecessary replication and avoid vendor lock-in with a virtualization-first approach.
Ensured Consistency Across Platforms
Define logic once—then use it across every analytics and AI workflow.
Future-Proofed Architecture
Flexibly support evolving data strategies without being tied to a single vendor or platform.
Ideal for:
Enterprises running analytics across AWS, Azure, and GCP.
Organizations migrating to the cloud in stages.
Data teams maintaining both cloud-native and legacy on-prem systems.
Companies standardizing access to metrics and data products across business units.
