Microsoft Fabric IQ: The Foundation Data Architects Need to Know

Microsoft Fabric IQ reached general availability at Build 2026, turning what was a preview into a platform architects now need to design around. This breakdown covers Fabric IQ’s five components: Ontology, Graph, Data Agent, Operations Agent, and Semantic Model. How they reinforce one another, and the governance decisions data architects need to make now that…

Building AI Systems with Databricks Multi-Agent Supervisor

Enterprise AI has evolved beyond simple chatbots answering single questions. Modern organizations need AI systems that can handle complex queries spanning multiple data sources, domains, and knowledge types. The Supervisor Agent (Databricks’ orchestration layer for coordinating specialized AI agents, now generally available) addresses this challenge by orchestrating specialized AI agents into a coordinated system that…

Snowflake Cortex Agents: Structured and Unstructured Data

Enterprise AI faces a fundamental trust problem. While language models generate fluent responses, users increasingly question whether those answers are actually true. The solution is not more sophisticated text generation. Instead, the answer is intelligent orchestration of verified data sources with quality measurement. Snowflake Cortex Agents solve this through a three-tier architecture that automatically routes…

Maximizing Power BI Copilot: A Data Analyst Guide to AI-Ready Semantic Models

Overview of Copilot in Power BI Imagine asking your data a question in plain English and getting an instant, accurate answer. That’s the promise of Power BI Copilot as a generative AI assistant that can transform how users interact with business intelligence. Rather than clicking through menus or building complex queries, users can simply type…

MCP: Meeting Business Users Where They Are

MCP with Query Capabilities Model Context Protocol (MCP) represents a paradigm shift in how data professionals deliver analytics to business users. At its core, MCP transforms the traditional analytics workflow by enabling Data Engineers and Data Analysts to encode their domain observations into structured prompts, resources, and tools that power intuitive, conversational interactions. The Observation-to-Context…

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