End-to-end tutorials in Microsoft Fabric

In this article, you find a comprehensive list of end-to-end tutorials available in Microsoft Fabric. These tutorials guide you through a scenario that covers the entire process, from data acquisition to data consumption. They're designed to help you develop a foundational understanding of the Fabric UI, the various experiences supported by Fabric and their integration points, and the professional and citizen developer experiences that are available.

Multi-experience tutorials

The following table lists tutorials that span multiple Fabric experiences.

Tutorial name Scenario
Lakehouse In this tutorial, you ingest, transform, and load the data of a fictional retail company, Wide World Importers, into the lakehouse and analyze sales data across various dimensions.
Data Science In this tutorial, you explore, clean, and transform a taxicab trip semantic model, and build a machine learning model to predict trip duration at scale on a large semantic model.
Real-Time Analytics In this tutorial, you use the streaming and query capabilities of Real-Time Analytics to analyze the New York Yellow Taxi trip semantic model. You uncover essential insights into trip statistics, taxi demand across the boroughs of New York, and other related insights.
Data warehouse In this tutorial, you build an end-to-end data warehouse for the fictional Wide World Importers company. You ingest data into data warehouse, transform it using T-SQL and pipelines, run queries, and build reports.

Experience-specific tutorials

The following tutorials walk you through scenarios within specific Fabric experiences.

Tutorial name Scenario
Power BI In this tutorial, you build a dataflow and pipeline to bring data into a lakehouse, create a dimensional model, and generate a compelling report.
Data Factory In this tutorial, you ingest data with data pipelines and transform data with dataflows, then use the automation and notification to create a complete data integration scenario.
Data Science end-to-end AI samples In this set of tutorials, learn about the different Data Science experience capabilities and examples of how ML models can address your common business problems.
Data Science - Price prediction with R In this tutorial, you build a machine learning model to analyze and visualize the avocado prices in the US and predict future prices.
Application lifecycle management In this tutorial, you learn how to use deployment pipelines together with git integration to collaborate with others in the development, testing and publication of your data and reports.