Getting Started With Microsoft Fabric | Part 1 | Learn Microsoft Fabric [2026]
Welcome to Part 1 of Learn Microsoft Fabric With Me [2026]. This introductory lesson sets the foundation for the learning journey ahead and explains how the series is structured for anyone looking to build a practical understanding of Microsoft Fabric. In this video, I cover: An introduction to the learning series Who this material is designed for What the overall learning journey will cover The series is aimed at beginners, professionals learning Microsoft Fabric for work, students, data practitioners, and anyone looking to better understand how the different capabilities within Microsoft Fabric fit together. Throughout the series, we will progressively explore Microsoft Fabric concepts, workloads, architectures, and hands-on implementations across the platform. The goal is simple: learn Microsoft Fabric practically, step by step, while building a clear understanding of the platform as a whole. This first lesson serves as the starting point and learning roadmap for everything that follows. watch?v=CXn98L8HSR0Microsoft Fabric Copy Job Tutorial for Beginners
In this beginner-friendly tutorial, I explain how to create and configure a Copy Job in Microsoft Fabric step by step — from source connection to destination loading. What is Copy Job in Microsoft Fabric Why Copy Job is important for Data Ingestion How to configure Source & Destination Step-by-step demo Best practices for beginners By the end of this video, you will confidently create your own Copy Job in Fabric. Thank you!! watch?v=mmZSvks32bg?si=s7ulM6OTk2eVg0h1
Location-Based Insights in Microsoft Fabric for Spatial BI & Analytics
Data teams excel at answering what happened and when, but many important questions also depend on where. In this session, we'll explore how spatial thinking extends analytics workflows in Microsoft Fabric and Power BI using Esri-powered GeoAnalytics capabilities available across the Fabric ecosystem. You'll see how location context enriches existing datasets, surfaces patterns that are invisible in tables and standard charts, and supports better decisions across operations, risk, and customer analytics. We'll walk through practical scenarios that connect Fabric data with ArcGIS data and map visuals, all from a BI-first perspective. No GIS background required. If you already work in Fabric or Power BI, this session will show how to add location-based insight to your analytics workflow using the tools you already know. Featuring the expertise of Philippa Burgess: / philippaburgess Get to know our moderators! / ladislau-andré-data-analyst / shalomandre 📌 This event is a part of a series, learn more here: https://aka.ms/FDD/Monthly Chapters: 00:06 Welcome & Housekeeping 00:59 Session Topic & Speaker Intro 03:53 Esri + Microsoft Fabric Partnership 05:36 Why Geospatial Data Matters 06:18 Types of Maps & Spatial Analysis 08:44 Microsoft Fabric Overview 10:05 Demo: Mapping in Fabric (No GIS Required) 11:10 Spatial Data Basics (Points, Lines, Polygons) 13:17 Spatial BI: Adding the “Where” 14:51 Architecture: Esri + Fabric Integration 16:26 Mapping Concepts Simplified 18:30 Spatial Analytics Across Microsoft Tools 22:10 Fabric Native Spatial Tools 23:24 GIS vs BI: Roles & Boundaries 24:15 Spatial Joins & Proximity Analysis 25:49 Heat Maps, Hotspots & Statistics 27:33 Spatiotemporal Analysis 30:15 Spatial Data Medallion Architecture 31:17 Getting Started with Spatial BI 36:24 Build Your Spatial Skills 38:48 Licensing & Access Options 41:30 Community & Learning Resources 45:04 Q&A 48:07 Fabric Data Days & Community Panel 58:52 Closing Remarks #MicrosoftReactor #learnconnectbuild [eventID:26607] watch?v=2M1vPfyxgdIMicrosoft Fabric Dataflow Gen1 Complete Tutorial | Creation, Transformations & Reporting | Episode 2
Welcome to Episode 2 of the Microsoft Fabric Dataflow Learning Series from NextGen Data Aspirants Community. In this session, we take a deep dive into Dataflow Gen1 and explore its complete workflow through live demonstrations in the Microsoft Fabric environment. If you find this content useful, please Like, Share, and Subscribe to NextGen Data Aspirants Community for more Microsoft Fabric, Power BI, Data Engineering, and Analytics content. watch?v=oVqd-F6-65A?si=CYrAQmRmq12JLQA4
DP-600 Exam Review Questions 81 to 90 Microsoft Exam for Fabric Analytics Engineer Associate part 9
DP-600 Exam Review Questions 81 to 90 Microsoft Exam for Fabric Analytics Engineer Associate Part 9 "Welcome back to our DP-600 Exam Review series for the Microsoft Fabric Analytics Engineer Associate certification. In this video, we’ll be diving into Part 8, covering Questions 81 to 90. These are mapped to Questions 31 through 40 in our ongoing memory-based review, ensuring you get a structured walkthrough of the most critical exam scenarios. We’ll explore advanced topics like Direct Lake memory optimization, Fabric capacity metrics monitoring, query folding in Power Query, PySpark broadcast join strategies, OneLake fine-grained access control, and governance with Microsoft Purview. Each question is designed to sharpen your understanding of real-world challenges—whether it’s scaling workloads, enforcing security boundaries, or optimizing data pipelines. By the end of this session, you’ll not only reinforce your exam readiness but also gain practical insights that apply directly to enterprise-scale analytics solutions in Microsoft Fabric. Let’s jump right into Questions 81 to 90 and continue building your mastery step by step." watch?v=DVW28_le2AQDP-800 Developing AI Enabled Database Solutions Exam Overview
🎬 DP‑800 Exam Overview "Welcome to this video! Today we’re giving you a clear overview of the Microsoft DP‑800: Developing AI‑Enabled Database Solutions exam. This certification is designed for professionals who want to demonstrate expertise in building modern, intelligent database solutions across SQL Server, Azure SQL, and Microsoft Fabric. We’ll walk through the exam format, skills measured, and key focus areas — from advanced T‑SQL and database design, to security and optimization, and finally to integrating AI capabilities like embeddings, vector search, and retrieval‑augmented generation. By the end of this video, you’ll have a solid understanding of what DP‑800 covers, how it’s structured, and how you can prepare effectively to earn this certification." watch?v=_pkJ8hjFaY4DP-600 Exam Review Questions 61 to 70 Microsoft Exam for Fabric Analytics Engineer Associate part7
🚀 DP-600 Exam Prep Part 7: Real-Time Intelligence, OneLake Shortcuts & Medallion Architecture (Questions 61–70) Preparing for the Microsoft Certified: Fabric Analytics Engineer Associate (DP-600) exam? In Part 7 of our practice question breakdown, we walk step-by-step through Questions 61 to 70, breaking down technical concepts, key Fabric features, and the exact reasoning behind correct and incorrect answers! 📌 Questions Covered Question 61: Real-Time Intelligence & Eventstream Routing (Branching streams into Lakehouse Delta tables vs. KQL Database without code) Question 62: OneLake Shortcut Types & Storage Optimization (Amazon S3, ADLS Gen2, internal shortcuts, and Direct Lake compatibility) Question 63: DAX Variable Optimization & Context Transition (Optimizing contribution percentages using VAR, ALL, and DIVIDE) Question 64: Dataflow Gen2 vs. PySpark Notebook Selection (Choosing low-code Power Query online for non-technical business analysts) Question 65: Medallion Architecture Implementation (Defining responsibilities across Bronze, Silver, and Gold layers) Question 66: Lakehouse SQL Analytics Endpoint Maintenance (Troubleshooting Delta log metadata synchronization and query latency) Question 67: CI/CD & Git Integration in Fabric (Native Git serialization for Semantic Models, Reports, and Notebooks) Question 68: Managing Large Dimension Tables in Direct Lake Models (VertiPaq memory optimization, removing high-cardinality columns, integer compression) Question 69: Partitioning Strategies & Liquid Clustering in Delta Lake (Accelerating daily filtering queries and consolidating small Parquet files with OPTIMIZE) Question 70: T-SQL Data Warehouse Constraints & Capabilities (Understanding non-enforced Primary/Foreign keys and optimizer hints in Fabric Data Warehouse) 🔑 Key Takeaways for the DP-600 Exam Eventstream Routing: Branching streaming payloads directly within the Eventstream UI allows zero-code routing to multiple destinations (e.g., Lakehouse for trends, KQL Database for alerts). OneLake Shortcuts: Shortcuts are zero-copy virtual pointers. Deleting a shortcut does not delete source data, and running OPTIMIZE V-Order on external ADLS Gen2 shortcuts does not rewrite external files. Medallion Architecture: Bronze: Raw, immutable, append-only landing zone. Silver: Cleansed, deduplicated, and conformed Delta tables. Gold: Aggregated star-schema models (Facts & Dimensions) optimized for Direct Lake reporting. Direct Lake Optimization: To prevent VertiPaq memory exhaustion, remove unused high-cardinality text columns and store numeric keys/identifiers as integers rather than strings to maximize compression. Fabric Warehouse Constraints: Primary and Foreign Keys in Fabric Data Warehouse are NOT ENFORCED during runtime loads; however, declaring them provides essential metadata for the T-SQL query optimizer to optimize joins. 📚 Resources & Links 📖 Microsoft Learn: Fabric Analytics Engineer Study Guide (DP-600) 🛠️ Microsoft Fabric Documentation 📺 Watch Full DP-600 Exam Preparation Series Playlist (Add link) 💬 Community & Questions Got questions on Direct Lake limits, Delta Liquid Clustering, or Git integration? Leave a comment below, and let's discuss! Don't forget to Like, Subscribe, and hit the Bell Icon to stay updated for Part 8! #MicrosoftFabric #DP600 #Azure #PowerBI #DataEngineering #Lakehouse #KQL #DeltaLake #DataflowGen2 #DAX #Certifications watch?v=QfbnicZSq6I
Fabric Monday 120: Using SCD with Master Data in Plan Objects
📋 Master data changed. Should the old value disappear? This week's Fabric Monday continues the demo from episode 116. Last time: maintaining master data with Plan Objects. This time: adding SCD to that maintenance process. ⚙️ I show how to configure SCD for master data in the Plan Object. ⚙️ Then the Plan Object manages the SCD behavior automatically while the data is maintained. ⚙️ Instead of simply overwriting values, the process preserves the historical versions. That is the interesting part: The business user keeps working in the Plan Object. The history is handled as part of the process. watch?v=cIq8mlMC820Fabric Monday 12: Chat with your Data using Fabric, OpenAI and Semantic Kernel
On this video you will discover how to use OpenAI and Semantic Kernel to chat with your data and get the answers you need. This can be done not only on notebooks, but the video also discuss some app architectures to be built for an end user. watch?v=dSQr1BgeIuIDP-600 Exam Review Questions 51 to 60 Microsoft Exam For Fabric Analytics Engineer Associate Part 6
🚀 Master Microsoft Fabric & Pass the DP-600 Exam! In this comprehensive practice guide, we walk through 10 high-impact, real-world scenario questions covering the core domains of the DP-600: Implementing Analytics Solutions Using Microsoft Fabric. Whether you're preparing for your certification or architecting enterprise data solutions on Fabric, this video breaks down complex concepts with detailed explanations for every correct and incorrect answer. --- 📌 TOPICS COVERED IN THIS PRACTICE SET: • Question 1: Optimizing Direct Lake Performance (V-Order, File Sizing & Cardinality) • Question 2: Workspace Lifecycle Management & Deployment Pipelines • Question 3: Choosing Ingestion & Transformation Orchestration • Question 4: Optimizing Apache Spark Notebook Performance (Data Skew & Salting) • Question 5: Granular Security (RLS, CLS & OneLake Data Access Roles) • Question 6: Managing Fabric Capacity Metrics, CU Smoothing & Throttling • Question 7: Delta Lake Time Travel, Retention & VACUUM Safety • Question 8: Cross-Database Querying via SQL Analytics Endpoint • Question 9: High-Performance Fabric Data Warehouse vs. Lakehouse Selection • Question 10: Advanced DAX Performance Tuning (Formula Engine vs. Storage Engine) --- 💡 KEY CONCEPTS & SKILLS VERIFIED: • Direct Lake vs. DirectQuery fallback triggers & memory optimization • Parametrization & Deployment Pipeline Rules in Microsoft Fabric • Fabric Data Pipelines vs. Dataflows Gen2 vs. PySpark Notebooks • Spark execution tuning: Addressing data skew with key salting and broadcast joins • Granular security enforcement (RLS, CLS, OLS) across SQL Analytics Endpoints & OneLake • Understanding Capacity Unit (CU) smoothing windows (5-min interactive vs. 24-hr background) • Delta Lake point-in-time recovery using Time Travel & `VACUUM` best practices • Cross-Lakehouse 3-part naming T-SQL queries • Choosing between Fabric Data Warehouse and Fabric Lakehouse architectures • Pushing DAX measure evaluation from Formula Engine (FE) to VertiPaq Storage Engine (SE) 👍 Enjoyed the video? Don't forget to LIKE, SUBSCRIBE, and hit the NOTIFICATION BELL 🔔 to stay updated with more enterprise data engineering, Microsoft Fabric, and Power BI content! 💬 Have questions about a specific question? Drop your thoughts in the comments below! #MicrosoftFabric #DP600 #PowerBI #DataEngineering #DirectLake #PySpark #DAX #DeltaLake #Azure #FabricCapacity #Certification watch?v=qFevuvSMArs
