Lets Learn Microsoft Fabric

Copilot, Power BI, Lakehouse, Direct Lake Mode and more

What you'll learn

The students will learn how to start using Microsoft Fabric to build a solution End to End including the use of Copilot to help.

In 2 weeks you will be able to at least get the data, ingest, transform and create a Power BI report.

No risks at all.

After the course I will give you my contact so we can connect offline and work together in a real case.

Requirements

Have a Base Knowledge in Databases.

Description

In this fascinating course you will be able to learn everything about how to use Microsoft Fabric from the beginning using all the modules of the tool including Copilot. From Getting Data, let's learn all the different ways to do it, also work with few external connectors to showcase all the different ways we can implement it. I will teach you how to configure the refresh of pipelines to run automatically notebooks, etc., in order to populate the PBI reports automatically. I will also teach you how to connect a Power BI report from Power BI desktop to the SQL analytic endpoint if you prefer to use import mode or direct query mode. Then using Copilot for the different experiences we will be able to transform data, create Python notebooks, correct errors in sql queries, create Power BI reports from scratch using natural language and more. Not only that , we will also create data in Real Time and use them in the Power BI report. With the new concept of having everything included in one place I will also show u the possibility of connecting data between different workspaces and work with RLS, CLS and data masking in data warehouse. After you finish this course you will have all the necessary tools to build your own. data model in Microsoft Fabric.

Overview

Section 1: Introducción

Lecture 1 Microsoft Fabric Introduction

Section 2: Data Engineering

Lecture 2 Create a Table in Lakehouse using a CSV.

Lecture 3 Medallion Architecture

Lecture 4 Shortcuts

Lecture 5 SQL Analytics Endpoint

Data Engineers and Data Analysts.