On-Demand Webcast
Ontology for Enterprises: Turn Siloed Data into a Business Intelligence Layer
Your organization already has the data. The challenge is connecting it with the relationships, rules, and business context needed to answer real questions.
Watch this webcast to learn how an enterprise ontology creates a shared intelligence layer across systems, documents, and organizational knowledge, helping business teams and AI work with consistent meaning.
What is enterprise ontology, and why does it matter?
An enterprise ontology is a living model of how your business works. It connects entities such as customers, products, suppliers, plants, orders, and shipments with their relationships, definitions, rules, and supporting information.
Consider a simple question: Why was this shipment delayed?
The answer may be distributed across an ERP system, operational dashboards, emails, Teams conversations, and supplier agreements. The information exists, but the context is disconnected.
An ontology-driven business intelligence layer brings these connections together, making information easier to understand, investigate, and act on.
What you’ll learn and see
In this webcast, you’ll learn how organizations can:
- Connect siloed enterprise data across business systems, documents, emails, and collaboration platforms
- Create a semantic business layer based on shared entities, relationships, rules, and definitions
- Help AI agents provide contextual, explainable, and source-backed answers
- Perform natural-language analysis, root-cause investigations, and what-if scenarios
- Use Fabric IQ, Foundry IQ, Work IQ, and Web IQ to bring together operational, organizational, document, and external context
- Practical demonstration showing how business users can ask questions in plain English and receive connected insights across operations, manufacturing, and supply chain scenarios.
See Enterprise Ontology in Action
The webcast includes a practical demonstration of how business users can ask questions in plain English and receive connected insights across operations, manufacturing, and supply chain scenarios.
See how ontology can support:
- Natural-language analysis
- Root-cause investigation
- Connected enterprise search
- Context-aware copilots and agents
- Traceable, better-informed decisions
Meet the Speaker
Poonam Chug, VP – Business Unit Head (Migration and Modernization) at Acuvate, helps enterprises accelerate cloud migration and modernization initiatives. With extensive experience in enterprise sales and digital transformation, she partners with organizations to deliver practical modernization strategies that drive business outcomes.
Enterprise Ontology – FAQs
An enterprise ontology is a structured model of a business’s entities, relationships, rules, definitions, and actions. It gives data a shared business meaning that both people and AI systems can understand.
Ontology connects information around common business entities, such as products, customers, suppliers, plants, and shipments. This allows related data from systems, documents, emails, and collaboration tools to be explored together.
An ontology-driven business intelligence layer adds business meaning and relationships to enterprise data. It helps users understand not only what happened, but also why it happened, what is affected, and what action may be required.
Ontology gives AI agents access to agreed business definitions, relationships, policies, and source information. This helps them provide responses that are more contextual, explainable, traceable, and aligned with business rules.
Yes. Once the relevant data and business context are connected, users can ask questions in plain language and receive answers grounded in the organization’s data, documents, relationships, and rules.
Microsoft IQ connects context from operational data, enterprise documents, organizational knowledge, and the external web through Fabric IQ, Foundry IQ, Work IQ, and Web IQ.
No. Organizations can begin with one high-value domain or business challenge, validate the value, and gradually extend the ontology to additional entities, data sources, and use cases.