Uploaded August 2026 | Updated September 2026, 2 weeks ago
Join a Microsoft’s very own Data Engineering team member on the SQL Server team on how their team uses Microsoft Fabric with Copilot CLI, VSCode Devcontainers, dbt (Data Build Tool) and more to remove coding barriers, automating repetitive tasks, have robust dev/test automation and enable platform engineers to focus on optimizing data stacks and architectures to unlock faster insights and greater value from data.
P.S. Ralph Wiggum from the Simpson’s TV show may also make a surprise appearance
🔗 This event is part of a series: https://aka.ms/DataDayslive/spark
0:00 Introduction and Speaker Overview
2:29 Agenda and AI-Native Data Engineering Overview
5:25 Modern Data Architecture (Vendor Agnostic)
6:42 Bronze, Silver, and Gold Data Zones
9:55 Introduction to dbt (Data Build Tool)
16:20 Declarative vs. Imperative Orchestration
20:30 Pillar of dbt: Don't Repeat Yourself (DRY)
21:46 Leveraging LLMs with dbt
26:10 Minimizing Custom Code with Spark
28:00 Spark Streaming and Incremental Processing
32:54 Local Development and Dev Containers
36:20 OneLake and Local Development Environment
39:35 "Ralph Wiggum" Loop Engineering Concept
43:08 Demo: Real-world Use Case in VS Code
51:46 Walkthrough of the Spark Diagnostic Silver Loader
58:05 Summary and Final Wrap-up
[eventID:27472]
Join a Microsoft’s very own Data Engineering team member on the SQL Server team on how their team uses Microsoft Fabric with Copilot CLI, VSCode Devcontainers, dbt (Data Build Tool) and more to remove coding barriers, automating repetitive tasks, have robust dev/test automation and enable platform engineers to focus on optimizing data stacks and architectures to unlock faster insights and greater value from data.
P.S. Ralph Wiggum from the Simpson’s TV show may also make a surprise appearance
🔗 This event is part of a series: https://aka.ms/DataDayslive/spark
0:00 Introduction and Speaker Overview
2:29 Agenda and AI-Native Data Engineering Overview
5:25 Modern Data Architecture (Vendor Agnostic)
6:42 Bronze, Silver, and Gold Data Zones
9:55 Introduction to dbt (Data Build Tool)
16:20 Declarative vs. Imperative Orchestration
20:30 Pillar of dbt: Don't Repeat Yourself (DRY)
21:46 Leveraging LLMs with dbt
26:10 Minimizing Custom Code with Spark
28:00 Spark Streaming and Incremental Processing
32:54 Local Development and Dev Containers
36:20 OneLake and Local Development Environment
39:35 "Ralph Wiggum" Loop Engineering Concept
43:08 Demo: Real-world Use Case in VS Code
51:46 Walkthrough of the Spark Diagnostic Silver Loader
58:05 Summary and Final Wrap-up
[eventID:27472]
![Get Certified: (Exam Day) What to Expect and How to Pass (US/EMEA)
Getting ready for exam day? This session is all about helping you walk in prepared and walk out confident.
We will break down what the exams are really like, including the types of questions you will see, how they are structured, and what can catch people off guard. You will hear directly from people who have taken and passed these exams, so you get real insight into what works and what does not.
We will also share practical strategies for studying, managing your time during the exam, and staying focused when it counts. Whether you are just starting your prep or getting close to test day, this session will help you feel ready.
📍 This session is a part of a series. Learn more here: https://aka.ms/datadayslive/cert-y
Chapters:
0:00 Intro & Welcome
0:48 Session Agenda Overview
8:46 How to Schedule Your Exam
16:17 Understanding Exam Formats
20:36 Exam Day: What to Expect
27:15 During the Exam: Navigation & Strategy
35:05 Tips for Efficiency & Time Management
38:47 Proctored Testing vs. Testing Centers
43:31 Live Demo: Official Study Resources
48:21 Live Demo: Exam Sandbox Experience
52:20 Strategies for Case Study Questions
57:25 Final Preparation Recap & Recommendations
#MSFTReactor #learnconnectbuild #DataDays #GetCertified
[eventID:27216] Get Certified: (Exam Day) What to Expect and How to Pass (US/EMEA)](https://i.ytimg.com/vi/oOyWUoRTFBc/mqdefault.jpg)
![Model Mondays - Spotlight On Model router in Microsoft Foundry
AI agents rarely rely on a single model to solve every task.
In this episode of Model Mondays, well explore how model router helps developers apply a hill-climbing approach to agent development by continuously finding better models for different steps in a workflow.
Learn how to evaluate models, compare performance across providers and model families, and dynamically route requests to the model best suited for each task.
Through discussions and demos, well show how model router helps agents improve quality, efficiency, and cost by treating model selection as an ongoing optimization process rather than a one-time decision.
- Explore the Resources - https://github.com/microsoft/model-mondays
- Read the Newsletter - https://aka.ms/model-mondays/newsletter
- Continue the conversation on the Discord - https://aka.ms/model-mondays/discord
0:00 - Introduction and Code of Conduct
0:59 - Welcome to Model Mondays
2:19 - Whats new in Model Router
3:06 - What is Model Router?
7:41 - Reducing latency and improving response precision
11:57 - How prompt routing works
17:58 - Updated list of available models
20:45 - Automatic model failover
24:14 - Policy enforcement in the routing stack
25:44 - Benchmarking the router
27:54 - Multiple agents, one model deployment
30:11 - What is hill climbing?
32:27 - Hill climbing with the model router
36:19 - Workshop: Can routing save money?
54:49 - Model Releases: How to build my optimization
1:04:24 - Weekly highlights in Microsoft Foundry
1:09:32 - Whats next week on Model Mondays
[eventID:27496] Model Mondays - Spotlight On Model router in Microsoft Foundry](https://i.ytimg.com/vi/od_WTpE2nH4/mqdefault.jpg)
![Fabric IQ y Ontología MCP: la capa semántica que entiende tu negocio
La sesión final lleva la serie al nivel más avanzado: la semántica empresarial como fundamento de todos los agentes.
Fabric IQ (GA desde Build 2026) es la capa de contexto compartido que unifica Data Agents, modelos semánticos y Ontologías sobre OneLake.
Aprenderás qué es una Ontología en Fabric, cómo define entidades, relaciones, propiedades y reglas de negocio vinculadas a datos en vivo, y cómo exponerla como servidor MCP para que cualquier agente externo — Claude, Copilot, agentes de Foundry — pueda fundamentar su razonamiento en ella sin reescribir integraciones.
Construiremos un flujo multi-agente completo donde el orquestador consulta la Ontología vía MCP para entender el negocio, delega al Data Agent para los datos, y entrega respuestas consistentes y gobernadas.
Cerraremos con una hoja de ruta práctica: qué está GA, qué está en Preview, y cómo planificar la adopción en tu organización hoy mismo. Los últimos 15 minutos serán Q&A abierto.
Trae tu caso de uso real — los últimos 15 minutos son para arquitectura personalizada y preguntas abiertas.
¿Qué es Fabric IQ?
https://learn.microsoft.com/fabric/iq/overview/?wt.mc_id=youtube_27357_organicsocial_reactor📌 Este evento es parte de una serie, aprende más aquí: https://aka.ms/AgentesFabric
[eventID:27357] Fabric IQ y Ontología MCP: la capa semántica que entiende tu negocio](https://i.ytimg.com/vi/os4zRz3esyM/mqdefault.jpg)
![New billing and capacity tools in Microsoft Fabric
Join our product experts for an interactive Q&A session on new billing capabilities in Microsoft Fabric.
With this new functionality, you can pay only for the compute you use across OneLake compute, Data Warehouse, and Spark, while automatically scaling resources up and down based on demand.
Well cover how these new capabilities work with your existing provisioned capacity, how to optimize costs for dynamic and bursty workloads, and the governance controls available to help you stay in control of usage and spend.
Bring your questions and get practical guidance on implementing them in your organization.
📌 This session is a part of a series! Learn more here: https://aka.ms/ATE/FabricEdition
[eventID:27488] New billing and capacity tools in Microsoft Fabric](https://i.ytimg.com/vi/p-l-xhZDY6Y/mqdefault.jpg)
![Build a Multi-Agent Career Copilot: Resume-to-Job Fit Analysis
Take the next step from a single agent to an orchestrated multi-agent workflow. Build a Resume-to-Job Fit Evaluator that processes a resume and job description, extracts requirements, scores alignment, identifies gaps, and creates a personalized learning roadmap with Microsoft Learn resources. Learnings: When a multi-agent workflow is more effective than a single agent How to split a larger task into specialized agents and reliable handoffs How to use MCP-enabled tools to enrich responses with Microsoft Learn content.
📌 This event is part of a series. Learn more here: https://aka.ms/FoundryToolkitVSCode/series
🔗 Learn more by exploring the resources:
https://aka.ms/FoundryToolkit/VSCode
https://aka.ms/FoundryToolkit/VSCode/Overview
[eventID:27524] Build a Multi-Agent Career Copilot: Resume-to-Job Fit Analysis](https://i.ytimg.com/vi/pEjeiIxr4fs/mqdefault.jpg)
![Build with AI: GitHub Copilot SDK for Building Agentic Workflows
AI can do more than assist with coding. It can help automate complex tasks and orchestrate intelligent workflows.
In this session, youll learn how to build real agent-driven workflows using GitHub Copilot SDK. Through a hands-on demonstration, youll see how AI can automate everyday development tasks, from issue management to code iteration, while coordinating tools, context, and multi-step execution. Discover how to move beyond writing code and start designing intelligent, task-driven workflows.
You Will Learn
• How to build agentic workflows using GitHub Copilot SDK
• How agents plan, reason, and execute multi-step tasks
• How to connect agents with tools, services, and external systems
• How to design intelligent workflows that automate everyday development processes
Technologies Used
• GitHub Copilot SDK
• Agent runtime (planning and multi-step execution)
• Model Context Protocol (MCP)
• Tool calling and integration
• Workflow orchestration
Who Should Attend
• Developers interested in building agent-driven solutions
• Engineers exploring GitHub Copilot SDK capabilities
• Platform and tooling builders creating intelligent workflows
• Anyone looking to move from AI-assisted coding to workflow automation
[eventID:27464] Build with AI: GitHub Copilot SDK for Building Agentic Workflows](https://i.ytimg.com/vi/pWZZrB-kaFU/mqdefault.jpg)
![¿Qué es MCP y por qué cambia todo en Microsoft Fabric?
La IA ya no solo responde preguntas: ahora ejecuta acciones sobre tus datos.
En esta sesión introductoria entenderás qué es el Model Context Protocol (MCP), por qué se ha convertido en el estándar de la industria y cómo Microsoft lo está integrando en Fabric como base de su plataforma agéntica.
Veremos la arquitectura cliente-servidor de MCP, qué son los servidores Local y Remote de Fabric, y cómo un agente de IA puede descubrir y operar workspaces, lakehouses y pipelines usando lenguaje natural. Sin código todavía — el objetivo es que salgas con el mapa mental completo del ecosistema.
¿Qué son los servidores MCP de Fabric?
https://learn.microsoft.com/rest/api/fabric/articles/mcp-servers/what-is-fabric-mcp-server/?wt.mc_id=youtube_27348_organicsocial_reactor
📌 Este evento es parte de una serie, aprende más aquí: https://aka.ms/AgentesFabric
0:00:03 - Introducción y bienvenida
0:03:47 - ¿Qué es MCP? (Teoría fundamental)
0:07:26 - Diferencias entre MCP Local y Remoto
0:12:44 - Mecanismos de transporte: Stdio vs. Streameable
0:18:23 - Primitivas del MCP: Tools, Resources y Prompts
0:26:09 - Mapa de servidores MCP en Microsoft Fabric
0:33:35 - ¿Qué instalar vs. qué conectar?
0:36:00 - Consumo de recursos, CU y tokens
0:41:05 - Microsoft Data Factory MCP
0:43:07 - RTI (Real Time Intelligence) MCP
0:45:36 - Data Activator MCP
0:47:17 - Operation Agent MCP
0:57:24 - Ontología y su rol en la IA
1:00:11 - Cierre y próximos pasos de la saga
[eventID:27348] ¿Qué es MCP y por qué cambia todo en Microsoft Fabric?](https://i.ytimg.com/vi/pjKnz7cgI5g/mqdefault.jpg)
![Building AI Agents with Microsoft Foundry and MCP Using Azure Logic Apps
Learn how to build AI agents with Microsoft Foundry and connect them to real-world business systems using the Model Context Protocol (MCP) and Azure Logic Apps.
In this session, well explore how MCP enables agents to discover and use tools, while Azure Logic Apps provides a secure, low-code way to integrate with enterprise applications and APIs. Through a live demo, youll see how to extend an AI agent beyond chat to retrieve data, automate workflows, and take action across your organization.
00:00 Welcome & Housekeeping
03:13 Session Overview: AI Agents with Microsoft Foundry, MCP & Azure Logic Apps
04:04 Speaker Introduction: Ziggy Zoleta
05:05 What Youll Build Today
05:50 What is Microsoft Foundry?
07:09 What is an AI Agent?
08:37 Understanding Model Context Protocol (MCP)
10:53 Why MCP + Azure Logic Apps Matters
12:18 Demo Architecture Overview
13:51 Creating Azure Resources & Storage
16:04 Creating a Microsoft Foundry Project
17:51 Deploying a GPT Model
19:34 Testing the Model in the Playground
20:30 Creating an Agent in Microsoft Foundry
22:16 Adding the Code Interpreter Tool
23:25 Connecting a Stock Market API
25:25 Testing Stock Price Retrieval
26:24 Creating Charts with Agent Tools
27:27 Building an Azure Logic App
30:20 Creating the Stock Storage Workflow
34:53 Testing the Logic App
36:51 Exposing the Workflow as an MCP Server
38:50 Connecting MCP to the Agent
41:04 Saving Stock Data with MCP
42:28 Multi-Stock MCP Demo
43:32 Combining API, MCP & Code
[eventID:27458] Building AI Agents with Microsoft Foundry and MCP Using Azure Logic Apps](https://i.ytimg.com/vi/q4MGGp9femg/mqdefault.jpg)
![Orchestrating Fabric Spark and Best Practices for Production-Ready Workload
Ready to take your Fabric Spark workloads from idea to production?
Join two members of the Microsoft product team as they walk through how to orchestrate Spark in Microsoft Fabric using proven, real-world best practices. This is your chance to learn directly from the people who build the product and see how these capabilities are designed to scale.
You’ll explore how to scale efficiently, improve price performance with native execution, and secure workloads with enterprise-grade features.
Walk away with a production-ready playbook, actionable steps, and AI-powered tools to confidently orchestrate Spark in Microsoft Fabric.
🔗 Register for Data Days: https://aka.ms/datadays
📍 This session is a part of a series, learn more here: https://aka.ms/DataDayslive/spark-y
Chapters:
0:00 Introduction
1:43 Agenda and Learning Pillars
3:50 Common Customer Challenges
5:01 Production Readiness & Compute Sizing
8:06 Billing Models: Fixed vs. Autoscale
15:40 Monitoring Workspace Usage
17:20 Compute Governance & Starter Pools
18:18 Security: Network, Encryption & Private Links
24:50 Performance Updates: Liquid Clustering & Native Execution
29:50 Pre-warm Clusters and Light Pools
30:51 Performance Tuning & Medallion Architecture
34:35 Adaptive Target File Sizes
37:44 Parallel Snapshot Loading & Connectivity Improvements
41:58 Identifying and Solving Data Skew
43:30 Memory Management & Avoiding Data Spills
44:40 Resource Profiles: Static vs. Auto-update
50:45 High Concurrency Mode and Orchestration
54:28 Importance of Testing & CI/CD
56:45 Early Release Channel
58:12 Library Management
59:25 JDBC/ODBC Connectivity & Livy API
1:01:28 Q&A Session
#MSFTReactor #learnconnectbuild
[eventID:27278] Orchestrating Fabric Spark and Best Practices for Production-Ready Workload](https://i.ytimg.com/vi/qNv7rSEVenY/mqdefault.jpg)
![Implementando seguridad y moderación de contenido
Conoce las mejores prácticas para asegurar aplicaciones de IA, incluyendo filtros, moderación de contenido y estrategias para mitigar riesgos y garantizar un uso responsable.
📍https://aka.ms/Microsoft.Extensions.AI
📌 Este evento es parte de una serie, aprende más aquí: https://aka.ms/MEAIseries
0:07 - Introducción y bienvenida
1:03 - Importancia de la seguridad en modelos de IA
2:12 - Conceptos teóricos: autenticación, moderación y monitoreo
3:21 - Controles y guardias de seguridad (Guardrails) en Azure AI Foundry
11:06 - Demostración: Configuración de filtros de contenido en el portal clásico
19:35 - Demostración: Configuración de controles en el nuevo portal de Foundry
31:11 - Demostración: Uso de listas de bloqueo personalizadas (Blocklists)
38:50 - Demostración: Manejo de excepciones en código
41:46 - Integraciones con proveedores de seguridad externos
45:47 - Demostración: Evaluaciones unitarias con Microsoft.Extensions.AI
56:17 - Cierre de la sesión
#microsoftreactor #learnconnectbuild
[EventID:27064] Implementando seguridad y moderación de contenido](https://i.ytimg.com/vi/qeHc9pRV5lw/mqdefault.jpg)
