AtScale, the main supplier of semantic layer expertise for analytics and AI, as we speak unveiled new product improvements and open requirements on the 2025 Semantic Layer Summit. The digital occasion introduced collectively over 5,000 information leaders to discover the way forward for ruled, AI-ready analytics.
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This yr’s keynote, introduced by AtScale Co-founder and CTO David Mariani, showcased the newest developments within the firm’s Common Semantic Layer Platform, together with:
- GenAI Platform Integrations: Energy reliable pure language analytics. AtScale now integrates natively with Databricks Genie and Snowflake Cortex Analyst, making certain that AI-generated insights align with enterprise definitions and governance insurance policies.
- One-Click on Modeling: Speed up mannequin creation with AI-powered automation. One-Click on Modeling intelligently scans your supply information to determine key metrics, dimensions, and relationships—eliminating handbook configuration and lowering time to worth.
- Composite Modeling: Allow decentralized collaboration with out compromising consistency. Composite Modeling permits groups to increase or inherit current fashions, making it straightforward to construct on shared definitions whereas sustaining a single supply of fact.
- Native PGWire Assist: Seamlessly connect with fashionable BI instruments. With inbound Postgres protocol assist, AtScale now gives plug-and-play compatibility with ThoughtSpot, Superset, Sigma, and extra—making certain easy integration throughout your analytics stack.
- Enhanced Energy BI Integration: Ship real-time insights with full governance. AtScale now helps native DAX and Tabular fashions in Energy BI, enabling a unified semantic layer expertise with stay connectivity, constant metrics, and no want for information duplication.
- In-Reminiscence Aggregates: Obtain sub-second question efficiency. This new caching characteristic shops aggregated question outcomes straight in reminiscence, accelerating response instances for even probably the most complicated analytical workloads.
“AI and analytics are converging quicker than ever—however with out semantics, there’s no basis for belief,” stated David Mariani, CTO and Co-founder of AtScale. “The improvements we introduced as we speak mirror our mission to present each group the facility to scale insights securely, persistently, and intelligently. From mannequin creation to AI integration, we’re delivering an entire platform for the following period of data-driven enterprise.”
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Driving Trade-Large Requirements By means of Open Supply
A central theme of the 2025 summit was an open customary for semantic standardization to stop semantic lock-in. AtScale formally launched the Semantic Modeling Language (SML)—the business’s first open-source language designed for outlining, sharing, and operationalizing semantic fashions. The SML GitHub repository now consists of:
- Prebuilt semantic fashions for TPC-DS, AdventureWorks, and Snowplow datasets
- A developer SDK for studying and writing SML programmatically
- CLI instruments for syntax validation, mannequin deployment, and ecosystem translation
Actual-World Influence: Prospects and Companions Take the Stage
The summit featured real-world tales from AtScale prospects who’re reworking enterprise analytics with semantic layers:
- House Depot showcased how AtScale’s semantic layer on BigQuery enabled enterprise-wide self-service in Excel, lowered time-to-insight, and delivered sub-second efficiency on a 20TB dice—powering a trusted, ruled basis for pure language analytics.
- TELUS demonstrated how semantic layers enabled scalable telecom community analytics by means of vendor abstraction and SML adoption.
- Vodafone Portugal, in partnership with Celfocus, shared how they migrated legacy OLAP programs to a contemporary cloud-native stack on Google Cloud—preserving acquainted BI workflows whereas boosting efficiency and governance.
- Blue Mercury and HSBC mentioned greatest practices for semantic layer implementation, aligning technical and enterprise groups round shared fashions and definitions.
The Way forward for Semantics within the Age of AI
The occasion closed with a forward-looking panel that includes leaders from Snowflake, IBM, Databricks, and ThoughtSpot, who mentioned the rising position of semantic layers in powering GenAI and redefining fashionable BI.
“Semantic layers aren’t only a pattern—they’re an important basis for reliable AI,” stated Bruno Aziza, Group VP of Knowledge, BI & AI at IBM. “As enterprises scale GenAI, the semantic layer is what brings governance, consistency, and enterprise context to each interplay.”
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