AtScale, the main supplier of semantic layer know-how for analytics and AI, at the moment 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.
Additionally Learn: AiThority Interview with Nicole Janssen, Co-Founder and Co-CEO of AltaML
This 12 months’s keynote, offered by AtScale Co-founder and CTO David Mariani, showcased the most recent 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 establish 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 present fashions, making it straightforward to construct on shared definitions whereas sustaining a single supply of reality.
- Native PGWire Assist: Seamlessly hook up with fashionable BI instruments. With inbound Postgres protocol help, AtScale now presents 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 instantly in reminiscence, accelerating response instances for even essentially the most advanced analytical workloads.
“AI and analytics are converging sooner 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 at the moment mirror our mission to provide each group the ability to scale insights securely, constantly, and intelligently. From mannequin creation to AI integration, we’re delivering a whole platform for the following period of data-driven enterprise.”
Additionally Learn: Why multimodal AI is taking up communication
Driving Business-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 trade’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: Clients and Companions Take the Stage
The summit featured real-world tales from AtScale clients who’re remodeling enterprise analytics with semantic layers:
- Residence Depot showcased how AtScale’s semantic layer on BigQuery enabled enterprise-wide self-service in Excel, diminished 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 via vendor abstraction and SML adoption.
- Vodafone Portugal, in partnership with Celfocus, shared how they migrated legacy OLAP methods to a contemporary cloud-native stack on Google Cloud—preserving acquainted BI workflows whereas boosting efficiency and governance.
- Blue Mercury and HSBC mentioned finest 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.”
[To share your insights with us, please write to psen@itechseries.com]
