Microsoft Fabric - A Deeper Dive

A deeper dive into data engineering, data science, real-time analytics, Power BI, Spark, Data Warehousing and more

What you'll learn

Power BI with DirectLake. A 170 million row fact table is used to demonstrate we don't need import mode any more!

Apache Spark Integration into Microsoft Fabric

Data science in Microsoft Fabric attempting to predict how long a taxi ride in New York City might take

Ingesting data using the power and flexibility of data pipelines with DataFlows Gen2 and Data Factory

Building a data warehouse in Microsoft Fabric

Building a real-time analytics solution using New York City taxi data and Event Streams with KQL

Semantic Link for Power BI

Requirements

There are no prerequisites for this course other than having some working knowledge of Microsoft Fabric. This is an intermediate level course.

Description

A deeper dive into what you might ask? A deeper dive than what our initial Microsoft Fabric course covers. We go more deeply into data engineering, data science, data warehousing, Spark, Power BI with DirectLake, Power BI with Semantic Link with end-to-end examples and studies. If you are a Power BI developer, you will love our deep dive into DirectLake where we use a 170 million row fact table to show that DirectLake is every bit as fast as tabular import mode. Hard to believe but true. We also cover Semantic Link with Power BI allowing Spark notebooks to interact with Power BI datasets.If data engineering is your specialty we go through and end-to-end project demonstrating how to use Dataflows Gen2 and Data Factory Copy Activity, with pipelines to build an ingestion process.If your interest is data science we go through an end-to-end machine learning project to demonstrate how Fabric and notebooks can be used or predict how long a taxi ride might take in New York City.If you have a need to learn more about real-time analytics and KQL, we go through a project where we simulate taxi data being ingested using event streams and KQL.If you are interested in building a data warehouse, we have an end-to-end data warehouse project showing how this can be done in Microsoft Fabric.Interested in Apache Spark? We cover the important areas of Spark and how it integrates into Microsoft Fabric.By the time you complete this 10+ hour course you will feel completely comfortable using all the most commonly used experiences in Microsoft Fabric.

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Exercises and Quizzes in this Course - Please Watch!

Lecture 3 Getting Started with Microsoft Fabric

Section 2: DirectLake and Power BI

Lecture 4 Overview - Part 1

Lecture 5 Overview - Part 2

Lecture 6 XMLA-Write Support

Lecture 7 Putting Direct Lake to the Test - Part 1

Lecture 8 Putting Direct Lake to the Test - Part 2

Lecture 9 Power BI Desktop and Direct Lake

Lecture 10 On-Demand Loading

Section 3: Data Science in Microsoft Fabric

Lecture 11 Introduction to Data Science

Lecture 12 Data Science in Microsoft Fabric

Lecture 13 Notebooks

Lecture 14 Experiments

Lecture 15 Models

Lecture 16 Preparing Data - Data Wrangling

Lecture 17 Building a Model - Ingesting Data

Lecture 18 Building a Model - Exploring and Visualizing the Data

Lecture 19 Building a Model - Cleaning and Preparing the Data

Lecture 20 Building the Model - Model Creation - Part 1

Lecture 21 Building the Model - Model Creation - Part 2

Lecture 22 Building the Model - Model Creation - Part 3

Lecture 23 Building the Model - Model Creation - Part 4

Section 4: Real-Time Analytics in Microsoft Fabric

Lecture 24 Introduction to Real-Time Analytics in Microsoft Fabric

Lecture 25 Event Stream

Lecture 26 Creating a KQL Database

Lecture 27 Creating an Event Stream

Lecture 28 Getting Location Data

Lecture 29 Adding the Data to the Lakehouse

Lecture 30 Exploring the Data

Lecture 31 More Data Exploration

Section 5: Data Factory in Microsoft Fabric

Lecture 32 Introduction to Data Factory in Microsoft Fabric

Lecture 33 Building a Pipeline - Part 1

Lecture 34 Building a Pipeline - Part 2

Lecture 35 Building a Pipeline - Part 3

Lecture 36 Building a Pipeline - Part 4

Lecture 37 Building a Pipeline - Part 5

Section 6: Data Warehouse in Microsoft Fabric

Lecture 38 Introduction to the Microsoft Fabric Data Warehouse

Lecture 39 Building a Data Warehouse - Part 1

Lecture 40 Building a Data Warehouse - Part 2

Lecture 41 Building a Data Warehouse - Part 3

Lecture 42 Building a Data Warehouse - Visual Query Builder

Lecture 43 Using Shortcuts to Analyze Data in a Lakehouse

Lecture 44 Modeling the Data and Auto-Generating a Power BI Report

Section 7: Apache Spark in Microsoft Fabric

Lecture 45 Introduction to Apache Spark in Fabric

Lecture 46 Spark Libraries

Lecture 47 Dataframe Basics - Part 1

Lecture 48 Dataframe Basics - Part 2

Lecture 49 Dataframe Basics - Part 3

Lecture 50 Common Operations with Dataframes

Lecture 51 Filtering Data

Lecture 52 Aggregating Data

Lecture 53 Joining Dataframes

Lecture 54 Working with Dates

Lecture 55 SQL Statements and Spark

Lecture 56 Machine Learning

Lecture 57 Microsoft Fabric 1.1. / Spark Runtime

Lecture 58 Spark Configuration

Section 8: Miscellaneous Topics

Lecture 59 Semantic Link for Power BI - Part 1

Lecture 60 Semantic Link for Power BI - Part 2

Lecture 61 Semantic Link for Power BI - Part 3

This is an intermediate level course on Microsoft Fabric. Some Fabric experience, or having taken another Microsoft Fabric introductory course, might be helpful