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In the last two years, most organisations have successfully deployed their first "Chat with your Data" pilots. These systems, built on Traditional RAG (Retrieval-Augmented Generation), are excellent librarians. If you ask, "What is our travel policy?", they can instantly find the PDF, read page 12, and summarise the allowance for dinner expenses. But what happens when you ask a question that requires reasoning, not just reading? "How will the delay in the supplier shipment from Shanghai impact our Q3 production targets for the Alpha product line, considering our current inventory levels?" A traditional AI will fail here. It will find documents mentioning "Shanghai," "Q3," and "Alpha," but it won't understand the causal chain. It sees words; it doesn't see the relationships between your supplier, your inventory, and your production schedule. To move from "AI that reads" to "AI that thinks," we need to upgrade from Vector Search to GraphRAG.

Modern BI platforms are evolving beyond traditional analytics. Qlik Cloud Analytics continues to innovate with features like Write Table, which allows users to input and manage data directly within Qlik apps. This insight explains what Write Table is, how it works, and how organizations can use it to add value in modern data architectures.

Microsoft's newest layer on Fabric that turns your data into a formal business model (ontology) that AI agents can understand and act upon. Still in preview with real limitations, but potentially game-changing for the right organizations.

The enterprise AI landscape has shifted from "Copilots" - chat-based assistants - to Agentic AI. At Microsoft Ignite 2025, this shift was formalized with Microsoft Foundry. This is not just a rebrand of Azure AI Studio; it is a fundamental re-architecture designed to move organizations from AI experimentation to an "AI Factory" model. For our customers, this means the ability to build fleets of autonomous agents that are secure, governed, and capable of executing complex business processes.

Databricks Agent Bricks accelerates AI agent development by automating evaluation, model selection, and governance—directly within your Databricks environment. Faster, cheaper, and secure, it helps enterprises scale AI beyond proof of concept and unlock real business value.