Lesson 81 of 81
Microsoft Fabric + AI: End-to-End Development Without Coding — Are Data Engineers at Risk?
Lessons81 lessons
- 1Microsoft Fabric: A Brief Introduction| What is Microsoft Fabric| One Lake| Integrated Analytics
- 2Unlock Microsoft Fabric on Power BI: A Complete Step-by-Step Guide to Starting Your Free Trial
- 3Microsoft Fabric Explained: What, Why, When & How to Use (Beginner Guide)
- 4Microsoft Fabric: Various Components| Microsoft Fabric Create Workspace, Lakehouse, Warehouse
- 5Microsoft Fabric: How to load data in Lakehouse using Dataflow Gen2| End to End Flow
- 6Microsoft Fabric: Load data in Warehouse- Dataflow Gen2| Note- Warehouse Destination available now
- 7Microsoft Fabric: How to load data in Warehouse using Data Pipeline | End to End Scenario
- 8Microsoft Fabric: How to load data in Lakehouse using Spark; Python using the notebook
- 9Microsoft Fabric: Do k-Means clustering in spark; analyze in Power BI | Integrated Machine Learning
- 10Microsoft Fabric: Create Date table Dataflow Gen2, use in Lakehouse, Warehouse| Time Intelligence
- 11Microsoft Fabric: How to load data in Lakehouse using Data Pipeline | End to End Scenario
- 12Microsoft Fabric: What are the options to load local files in Lakehouse
- 13Microsoft Fabric: Shortcut within Fabric and for Azure Data Lake| File vs Table Shortcut
- 14Microsoft Fabric: Import Azure SQL Data to Warehouse | Multiple tables using Pipeline
- 15Microsoft Fabric: Incremental ETL for Warehouse using Dataflow Gen 2, SQL Procedure, Data Pipeline
- 16Microsoft Fabric: Incremental ETL for Warehouse using Data Pipeline, SQL Procedure
- 17Microsoft Fabric: Load local SQL server data in Lakehouse using on-premise Gateway| Dataflow Gen2
- 18Microsoft Fabric: Power Query Transformations in Dataflow Gen2| Warehouse Destination | 2023 Update
- 19Microsoft Fabric: Load Azure SQL Data to Lakehouse & Warehouse simultaneously with Dataflow Gen2
- 20Microsoft Fabric: Load Snowflake DB Data to Lakehouse & Warehouse simultaneously with Dataflow Gen2
- 21Incremental ETL in Microsoft Fabric | Append Only New Data (No SQL, No Dataflow Gen2)
- 22Microsoft Fabric: Load local SQL server data in Warehouse using Python, Pandas, and sqlalchemy
- 23Microsoft Fabric: Load incremental data from local SQL server to Warehouse using on-premise Python
- 24Microsoft Fabric: Load on-premise data file to Lakehouse using on-premise Python using OAuth Token
- 25Microsoft Fabric: Use Token Authentication to load local SQL server to Warehouse using Python code
- 26#microsoftfabric: Use Token Authentication to load local SQL server to #lakehouse using Python code
- 27#microsoftfabric: Microsoft Fabric OneLake Explorer| Append Data in CSV| Simplified Python code
- 28#microsoftfabric: Microsoft Fabric OneLake Explorer or also an Azure Data Lake Explorer| Shortcut
- 29#microsoftfabric: DataWarehousing without Identity Column| Prompt Engineering in ChatGPT to Get ETL
- 30#microsoftfabric: Data Wrangling Using Notebook and Pandas Dataframe vs Dataflow Gen 2- Power Query
- 31#microsoftfabric #powerbi- Time Intelligence with Multi-Company Calendar/Date table| Duplicate Date
- 32Master Power Query Templates in Microsoft Fabric: Export & Import Data Flow Gen 2 | 2023
- 33#microsoftfabric- How to use Append data option of Data Flow Gen 2 and Data Pipeline| Incremental
- 34#microsoftfabric- How to Export data to external sources like Azure SQL and ADLS Gen2| Download Data
- 35#microsoftfabric #SQL- How to create Slowly Changing Dimension (SCD)| Create SCD in Microsoft Fabric
- 36Integrating Power BI & Synapse Data Science: Semantic Link in Microsoft Fabric | 2023 Tutorial
- 37#microsoftfabric: Create calculation group on custom dataset in Microsoft Fabric| Tabular Editor 3
- 38Microsoft Fabric: Unlocking Power BI Potential: Direct Lake on Warehouse| Nov 2023 and GA Updates
- 39Exploring Microsoft Fabric's Latest Feature: DeltaLake.Table M Function - Dec 2023 Update!
- 40Microsoft Fabric Event Streams: Real-Time Reflex Alerts with Raspberry Pi Simulator | Azure IoT Hub
- 41Microsoft Fabric/Power BI Update Jan 2024: Creating Calculation Groups in Semantic Model on Service
- 42Managing Microsoft Fabric Lakehouse using Spark SQL: Data Manipulation Insert, Update, Delete, Alter
- 43Microsoft Fabric: Maximize Data Performance: Delta Table Optimization with Fabric Notebooks
- 44Microsoft Fabric: Row Level Security in Direct Lake Semantic Model| Secure Data no access to OneLake
- 45Now Integrate On-Premise Data with Microsoft Fabric Using Data Pipelines: Gateway Update
- 46Explore the New Microsoft Fabric Folders Feature | Organize Like Never Before
- 47How to Migrate Custom Semantic Models in Microsoft Fabric Using ALM Toolkit| Data Migration Tutorial
- 48Microsoft Fabric Cost Breakdown: Capacity, Storage, Transfer & Azure Calculator| F64| Pay as you Go
- 49Microsoft Fabric: How to Buy Microsoft Fabric Capacity(Azure Portal) & Upgrade Seamlessly
- 50Meet Microsoft Fabric Expert: Pawel Potasinski| What next we can expect from Microsoft Fabric
- 51Microsoft Fabric Copilot Tutorial: How to use NLP in Data Flow Gen2| Unlock AI-Powered Data Analysis
- 52Microsoft Fabric Tutorial: Mastering Data Pipeline Semantic Model Refresh- when needed, how to use
- 53Microsoft Fabric Time Machine: Time travel in Fabric Warehouse| Historical Data with Time Travel
- 54Microsoft Fabric: How to Transfer Data from Fabric Lakehouse to Local System: Step-by-Step Tutorial
- 55Supercharge Your Data Analysis: DAX Calculated Columns & Tables in Microsoft Fabric (New Feature!)
- 56Microsoft Fabric Notebooks: Essential Functions for Data Analysis| Describe, filter, join, groupBy
- 57Create Field Parameters in Microsoft Fabric Custom Semantic Model using Calculated Table| SSMS| XMLA
- 58Microsoft Fabric Time Machine: Time travel in Fabric Lakehouse| Historical Data with Time Travel
- 59Microsoft Fabric- Embed Interactive Power BI Visualizations in Python Notebooks| Visualize Dataframe
- 60Microsoft Fabric Warehouse| Zero Copy Clone |Time Travel using Clone| How to Create & Manage Clones
- 61Microsoft Fabric: Introducing T-SQL Notebooks in Microsoft Fabric: Public Preview Tutorial
- 62Microsoft Fabric Copy Job: Simplify Data Movement| DP 600 | DP 700- Upsert not covered- New Feature
- 63SQL Database in Microsoft Fabric (2025)| Step By Step Guide: Dataflow Gen 2, Pipelines & Date Tables
- 64Microsoft Fabric Tutorial for Beginners (DP 700): Full Guide, Costs, Delta Parquet & How to Start
- 65Microsoft Fabric Domains Explained: What is Domain? | How to Create and Manage Domains Easily
- 66JSON Aggregate Functions in Microsoft Fabric: JSON_ARRAYAGG | JSON_OBJECTAGG
- 67Microsoft Fabric OneLake Shortcuts Explained | Access Data Across Capacities (Even When Paused)
- 68Microsoft Fabric Workspace Tutorial 2025: Create, Configure & Share | Full Setup Guide
- 69Direct Lake in Power BI: How to Create Direct Lake Semantic Models in Power Bi Desktop | MS Fabric
- 70Microsoft Analytics Conference 2025: Era of Microsoft Fabric, AI & Copilot
- 71Shifting Data Gravity to OneLake with Data Factory in Microsoft Fabric | Microsoft Fabric Tutorial
- 72Power BI Vendor Onboarding: Share Content, Connections & Gateways with External/Guest Users
- 73IDENTITY Columns in Microsoft Fabric Data Warehouse - Auto Generate Surrogate Keys Tutorial 2026
- 74Microsoft Fabric Surge Protection Explained | Workspace-Level Controls (Preview)
- 75Composite Semantic Models Explained | Direct Lake + Import Tables in Power BI (2026 Update)
- 76Microsoft Fabric: Connect Any Data Source Inside Notebook | Fabric Connection Feature 2026
- 77New Fabric Feature! Dataflow Gen2 New Destinations Explained(Excel, Snowflake) | Lakehouse, OneDrive
- 78Microsoft Fabric Tenant Settings Explained| Enable Fabric for Your Organization | Fabric Admin Guide
- 79You Can Create Calculated DAX Columns in Direct Lake — But Should You?
- 80Microsoft Fabric App + AI: End-to-End Development Without Coding — Are Data Engineers at Risk?
- 81Microsoft Fabric + AI: End-to-End Development Without Coding — Are Data Engineers at Risk?