<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Fabric End-to-End on Sam Debruyn</title><link>https://debruyn.dev/tags/fabric-end-to-end/</link><description>Recent content in Fabric End-to-End on Sam Debruyn</description><generator>Hugo</generator><language>en-us</language><copyright>© Copyright Debruyn Consultancy</copyright><lastBuildDate>Thu, 08 May 2025 09:01:52 +0200</lastBuildDate><atom:link href="https://debruyn.dev/tags/fabric-end-to-end/index.xml" rel="self" type="application/rss+xml"/><item><title>Fabric end-to-end use case: Analytics Engineering part 2 - Reports</title><link>https://debruyn.dev/2023/fabric-end-to-end-use-case-analytics-engineering-part-2-reports/</link><pubDate>Tue, 19 Sep 2023 20:59:15 +0200</pubDate><guid>https://debruyn.dev/2023/fabric-end-to-end-use-case-analytics-engineering-part-2-reports/</guid><description>&lt;p&gt;Welcome to the fifth part of a 5-part series on an end-to-end use case for Microsoft Fabric. This post will focus on the analytics engineering part of the use case.&lt;/p&gt;

&lt;p&gt;In this series, we will explore how to use Microsoft Fabric to ingest, transform, and analyze data using a real-world use case. The series focuses on data engineering and analytics engineering. We will be using OneLake, Notebooks, Lakehouse, SQL Endpoints, Data Pipelines, dbt, and Power BI.&lt;/p&gt;</description></item><item><title>Fabric end-to-end use case: Analytics Engineering part 1 - dbt with the Lakehouse</title><link>https://debruyn.dev/2023/fabric-end-to-end-use-case-analytics-engineering-part-1-dbt-with-the-lakehouse/</link><pubDate>Mon, 11 Sep 2023 09:59:11 +0200</pubDate><guid>https://debruyn.dev/2023/fabric-end-to-end-use-case-analytics-engineering-part-1-dbt-with-the-lakehouse/</guid><description>&lt;p&gt;Welcome to the fourth part of a 5-part series on an end-to-end use case for Microsoft Fabric. This post will focus on the analytics engineering part of the use case.&lt;/p&gt;

&lt;p&gt;In this series, we will explore how to use Microsoft Fabric to ingest, transform, and analyze data using a real-world use case. The series focuses on data engineering and analytics engineering. We will be using OneLake, Notebooks, Lakehouse, SQL Endpoints, Data Pipelines, dbt, and Power BI.&lt;/p&gt;</description></item><item><title>Fabric end-to-end use case: Data Engineering part 2 - Pipelines</title><link>https://debruyn.dev/2023/fabric-end-to-end-use-case-data-engineering-part-2-pipelines/</link><pubDate>Mon, 04 Sep 2023 09:59:04 +0200</pubDate><guid>https://debruyn.dev/2023/fabric-end-to-end-use-case-data-engineering-part-2-pipelines/</guid><description>&lt;p&gt;Welcome to the third part of a 5-part series on an end-to-end use case for Microsoft Fabric. This post will focus on the data engineering part of the use case.&lt;/p&gt;

&lt;p&gt;In this series, we will explore how to use Microsoft Fabric to ingest, transform, and analyze data using a real-world use case. The series focuses on data engineering and analytics engineering. We will be using OneLake, Notebooks, Lakehouse, SQL Endpoints, Data Pipelines, dbt, and Power BI.&lt;/p&gt;</description></item><item><title>Fabric end-to-end use case: Data Engineering part 1 - Spark and Pandas in Notebooks</title><link>https://debruyn.dev/2023/fabric-end-to-end-use-case-data-engineering-part-1-spark-and-pandas-in-notebooks/</link><pubDate>Mon, 28 Aug 2023 08:58:56 +0200</pubDate><guid>https://debruyn.dev/2023/fabric-end-to-end-use-case-data-engineering-part-1-spark-and-pandas-in-notebooks/</guid><description>&lt;p&gt;Welcome to the second part of a 5-part series on an end-to-end use case for Microsoft Fabric. This post will focus on the data engineering part of the use case.&lt;/p&gt;

&lt;p&gt;In this series, we will explore how to use Microsoft Fabric to ingest, transform, and analyze data using a real-world use case. The series focuses on data engineering and analytics engineering. We will be using OneLake, Notebooks, Lakehouse, SQL Endpoints, Data Pipelines, dbt, and Power BI.&lt;/p&gt;</description></item><item><title>Fabric end-to-end use case: overview &amp; architecture</title><link>https://debruyn.dev/2023/fabric-end-to-end-use-case-overview-architecture/</link><pubDate>Mon, 21 Aug 2023 09:59:15 +0200</pubDate><guid>https://debruyn.dev/2023/fabric-end-to-end-use-case-overview-architecture/</guid><description>&lt;p&gt;Welcome to the first part of a 5-part series on an end-to-end use case for Microsoft Fabric. This post will focus on the architecture overview of the use case.&lt;/p&gt;

&lt;p&gt;In this series, we will explore how to use Microsoft Fabric to ingest, transform, and analyze data using a real-world use case. The series focuses on data engineering and analytics engineering. We will be using OneLake, Notebooks, Lakehouse, SQL Endpoints, Data Pipelines, dbt, and Power BI.&lt;/p&gt;</description></item></channel></rss>