Investing in the semantic layer is crucial for enhancing data accessibility, expediting insights delivery, and ensuring KPI consistency. At AtScale, we're committed to empowering this ecosystem by offering avenues to kickstart semantic layer development, whether through our community edition, industry expertise collaboration, or seamless integration with our infrastructure. We prioritize partnerships with SIs and ISVs to grow the semantic layer and invite interested parties to join the AtScale Partner Program to drive innovation in data analytics.

By empowering an LLM with the logical context of a semantic layer, we can incorporate business terminology and logic into its responses and enable queries to the database using natural language ( instead of SQL). Coupling this with AtScale’s query engine results in increased performance in the face of Natural Language prompts from business users. In this talk we will explore an application of such a model, in the form of an LLM and Semantic Layer backed Chat Bot.

The hardest part of implementing an enterprise semantic layer is modeling the business’ data definitions. Integrating Generative AI with a Semantic Layer creates a robust, user-friendly way for organizations to accelerate semantic model creation deployed across the enterprise. In this session we’ll investigate how Google’s Gemini, leveraging a semantic layer, helps identify trends from onshore oil and gas production data from the Texas Railroad Commission. We’ll demystify technologies for those new to the generative AI or the semantic layer landscape by creating KPIs using the LLM for use in analytics workflows and dashboards.

As the field of data analytics continues to progress and expand, the role of semantic layers in harnessing the power of AI is becoming increasingly crucial. The incorporation of context and constraint is essential to optimizing the potential of Large Language Models (LLMs), which requires a more structured and specialized approach. While traditional methods have made strides in providing some context through prompt engineering and knowledge graphs, semantic layers offer unparalleled clarity and efficiency in bridging the gap for LLMs. To further unfold the narrative on semantic layers and their transformative impact on AI-enabled analytics, we invite you to a thought-provoking session with Artyom Keydunov, Cube's CEO & Co-founder at the Semantic Layer Summit.

The value of semantic layers for business intelligence is well-understood, and has been a focus of a host of innovations in the past decade. However, with the emergence of new classes of data-driven applications - native data applications, AI-driven insights, and analytic co-pilots - semantic layers are in a position to unlock even more value from enterprise data. In this session we will discuss the evolution of semantic layers for BI, along with the evolving set of modern analytical use cases that benefit from semantic layers.

As organizations seek to extract insights from a wider range of internal and external data sources, careful consideration of how best to enable consistent, effective and appropriate use becomes increasingly important. Using prebuilt semantic models, organizations can now tap into the expertise of the data providers to create a curated experience that steers analysts towards the insights the organization requires.

Today’s organizations grapple with an ever-increasing amount of data which makes it challenging to ensure all users operate from a current, single source of truth. Harris Associates has found a solution by leveraging a smart data fabric architecture enriched with a semantic layer. Join us as we share Harris Associates’ story, where technology meets strategic vision to deliver operational efficiencies.

Packaged analytics solutions such as GA4 have hindered a company's ability to derive insights due to latency and data quality issues. Through real-time streaming into your warehouse, Snowplow's rich behavioral data allows teams to surface in-depth learnings and improve decision making across marketing, product, and other areas of the business. Join our session with John Reid (Senior PM at Snowplow) as he showcases how Snowplow Digital Analytics orients around the warehouse and operationalizes additional workflows in the semantic layer and other parts of the technology stack.