AI Success Starts with AI-Ready Data

Since 2022, generative and agentic AI (GenAI, Agentic AI) have moved from research labs into everyday business. These technologies are designed for everyone in the enterprise without requiring deep technical skills or lengthy onboarding, which makes them powerful accelerators of productivity and automation. Their broad accessibility also introduces new risks.

This keynote highlights two critical areas that have become especially important as AI adoption accelerates:

1. Data Access: The Universal Semantic Layer

AI agents are highly capable. Without proper control, they can autonomously access, link, and move data across the enterprise, automatically and without human oversight. This creates tangible risks of data leakage, regulatory breaches, and unexpected costs.

The answer is a universal semantic layer: a controlled environment that centrally governs meaning, access, policies, and reuse of data objects for people, applications, and agents. It should support modeling and analytics with built-in AI capabilities while acting as a firewall that ensures AI agents only access what is permitted, traceable, and compliant.

Beyond risk mitigation, the universal semantic layer addresses the complexity of existing BI infrastructures. Large enterprises typically run multiple data sources and several BI tools, each with its own limited semantic layer. This leads to duplicated business logic and inconsistent definitions. Adding GenAI access multiplies entry points and increases chaos. A universal semantic layer unifies business models and access across tools, allowing organizations to retain and extend current BI investments at significantly lower cost.

2. Data Location: Data Repatriation

AI requires powerful servers, and enterprises must ensure secure access and compliance. With rising cloud costs, fluctuating capacity at hyperscalers, and tightening regulations around privacy and security, many organizations are moving workloads back on-premises or to local providers. This trend, known as data repatriation, aims to balance cloud flexibility with the control provided by private infrastructure.

This keynote sets the stage for the day: trusted AI outcomes require not only powerful algorithms but also a robust data architecture built on semantic consistency, sovereignty, and governance.

Highlights include:

• Strategic frameworks for leveraging AI across the enterprise.
• Key trends and technologies shaping intelligent business models.
• Introducing Strategy Mosaic, a universal semantic layer, providing governed and AI-optimised data access, open to BI tools, applications and AI agents. It eliminates data chaos through a unified source of truth for consistent insights across applications, ensures proven scalability with robust security and centralised business logic, and accelerates AI-ready models by enhancing data with semantic context.
• Introducing Strategy One, an enterprise AI+BI platform that delivers scalable intelligence across any cloud, with native AI integrations. Users effortlessly discover rapid insights, automate customised dashboard creation, and drive innovative analytics through intuitive, self-service tools. With governed semantic layers, it ensures a controlled, secure environment that streamlines workflows, minimises time to insight, and fosters agile, informed decision-making for all users.
• Best practices for integrating AI-driven decision-making into existing workflows.
• Success stories illustrating tangible business value through AI adoption.

Unlock the full potential of your business with actionable insights and proven strategies for implementing enterprise intelligence in the age of AI. Don’t miss this opportunity to gain a competitive edge for your organisation!

Michael Huber, Strategy
With nearly 20 years in business and over 16 years in the IT and cloud partner ecosystem, Michael is a seasoned Senior Alliance & Partner Management Professional with a strong record of driving growth and innovation in global matrix organizations. His experience spans leading tech companies such as Strategy (formerly MicroStrategy), Oracle, Exasol, Talend, Rackspace, and Microsoft, where he built and managed high-performing partner ecosystems across Europe. Recognized as a cloud evangelist and partner development expert, he combines strategic vision with deep ecosystem expertise to align partner strategies with corporate growth objectives and deliver measurable business impact.

Learn how Strategy Mosaic delivers a Universal Intelligence Layer that unifies data from multiple sources into a single semantic governance framework, ensuring a single version of truth for enterprise analytics.

The session will showcase:

• AI-Optimized Data Access: secure, tool-agnostic access to both structured and unstructured data.
• Mosaic Studio: AI-powered modeling that builds rich semantic models in minutes.
• Flexibility & Scalability: seamless movement across databases, BI tools, and cloud providers without costly transformations.
• Enhanced Decision-Making: consistent, real-time insights that eliminate silos and conflicting metrics.

A live demo will highlight how Strategy Mosaic simplifies data preparation and empowers faster, more reliable decisions across the enterprise.

AI initiatives require a data foundation that can keep up with speed and complexity. Exasol’s analytical engine provides the performance backbone for an AI-ready architecture, processing large data volumes at in-memory speed while maintaining governance, consistency, and predictable cost structures.

In this session, you will see how Exasol enables:

• High-Performance AI Analytics: accelerate complex queries and models with in-memory technology optimized for demanding AI workloads.
• Mission-Critical Scalability: scale across hybrid or on-premise environments without compromising speed or control.
• AI-Ready Data Architecture: provide a stable foundation to run advanced analytics and machine learning securely and reliably.
• Cost Optimization: reduce cloud dependency and maintain predictable performance at lower operational costs.

Exasol’s approach shows why AI success is not just about smarter models but also about smarter data architecture. This session highlights how enterprises can strengthen their analytical backbone to make AI initiatives faster and more trustworthy.

Dirk Beerbohm, Exasol
Dirk Beerbohm, a Global Partner Solution Architect at Exasol, supports global partners with over 30 years of expertise in data analytics. Specializing in structured, unstructured, and hybrid data, he focuses on machine learning and AI, particularly large language models. As Lead Solution Engineer for ML and AI, he bridges R&D and partner/customer needs.

As a second step you will learn how the data in an Exasol database can be queried by user without knowledge of the database design or the backend infrastructure - just by asking in natural language.

Dirk Beerbohm, Exasol
Dirk Beerbohm, a Global Partner Solution Architect at Exasol, supports global partners with over 30 years of expertise in data analytics. Specializing in structured, unstructured, and hybrid data, he focuses on machine learning and AI, particularly large language models. As Lead Solution Engineer for ML and AI, he bridges R&D and partner/customer needs.