Dp-700: Fabric Data Engineer Associate

Prepare yourself for the Microsoft Certified: Fabric Data Engineer Associate exam

What you'll learn

Students will learn how to build warehouse and lakehouses on Microsoft Fabric.

Students will learn all aspects required to take on the DP-700 exam.

Students will learn aspects around ingesting and transforming data into Microsoft Fabric.

Students will gain a better understanding on how to use Microsoft Fabric when it comes the data engineering needs.

Requirements

Students will learn about Microsoft Fabric from scratch. No prior knowledge is required, .

Students will need to create a trial Microsoft Fabric account and a free trial Azure Free account. This course showcases how to create both accounts.

Description

This intensive, comprehensive course is designed to prepare data professionals for the Microsoft DP-700 certification exam, focusing on data warehouse implementation and optimization using Microsoft Fabric. Participants will gain the knowledge and practical skills necessary to design, implement, and manage semantic models, data warehouses , lakehouses that leverage the full power of Microsoft's modern data analytics platform.What are we going to learnFirst we'll setup the required accounts and tools required to practice along. We will learn how to use Free trial licenses when it comes to Microsoft Fabric.Then we will do a deep-dive into hosting data warehouses in Microsoft Fabric. There are different ways in which we can ingest data into a data warehouse. We will learn how to use Data pipelines, T-SQL and Data Flow Gen2 to ingest data into a data warehouse. We won't be done there. We will learn how to design Fact and Dimension tables within a data warehouse.Next it will be time to perform a deep-dive into Lakehouses. We'll again use Data pipelines and Data Flow Gen2 to ingest data into a lakehouse. We'll learn on how to use Notebooks to in interact with data within a lakehouse.Next comes the Eventhouse. How do we get data into the eventhouse. How do we stream a continuous data streams into the eventhouse. And then how to use the Kusto Query Language to query for data.As per the exam , we need to focus on key security concepts, such as how to secure access to items in Microsoft Fabric. How do we enforce column and row level security. There's a lot to cover when it comes to security in Microsoft Fabric.

Overview

Section 1: Introduction

Lecture 1 The importance of data

Lecture 2 What are the tools and services we need to cover

Lecture 3 Using Azure as a cloud-based platform

Lecture 4 Creating the Azure Free Account

Lecture 5 Tour around the Azure Portal

Lecture 6 What is Microsoft Fabric

Lecture 7 Microsoft Fabric terms

Lecture 8 Note on Microsoft Fabric Licensing

Lecture 9 On-boarding ourselves onto Microsoft Fabric

Lecture 10 Getting Microsoft Fabric Trial capacity

Lecture 11 Installing Visual Studio Code

Lecture 12 Note on the data sets we are going to use

Section 2: Ingest and Transform data - Data warehouse

Lecture 13 Section Code

Lecture 14 The Data warehouse

Lecture 15 How is data modelled in a data warehouse

Lecture 16 How are we initially going to start building the data warehouse

Lecture 17 Lab - Microsoft Fabric - Creating a data warehouse

Lecture 18 Lab - Azure - Creating a Data Lake Gen2 storage account

Lecture 19 Lab - Microsoft Fabric - Data warehouse - Ingesting data via T-SQL

Lecture 20 Lab - Microsoft Fabric - Data warehouse - Ingesting data - Data Pipeline

Lecture 21 Lab - Microsoft Fabric - Data warehouse - Ingesting data - Dataflow Gen2

Lecture 22 Microsoft Fabric - Data warehouse - Our source of data for the fact table

Lecture 23 Quick look into our data sets

Lecture 24 Lab - Microsoft Fabric -Data warehouse - Data Flow Gen2 - Configuring the source

Lecture 25 Lab - Microsoft Fabric -Data warehouse -Data Flow Gen2 - Completing the workflow

Lecture 26 Lab - Microsoft Fabric - Data warehouse -Data Flow Gen2 - Building the dimension

Lecture 27 Lab-Microsoft Fabric -Data warehouse-Data Flow Gen2-Building the Date Dimension

Lecture 28 Lab - Microsoft Fabric - Ingesting data - Data Pipeline - Running the Dataflows

Lecture 29 Lab -Microsoft Fabric -Ingesting data -Data Pipeline -Running a stored procedure

Lecture 30 Lab - Data warehouse - Semantic Models - Creating a new workspace

Lecture 31 Lab - Data warehouse - Semantic Models - Transferring data onto the warehouse

Lecture 32 Lab - Data warehouse - Semantic Models - Building the semantic model

Lecture 33 Lab - Microsoft Fabric - Data warehouse - T-SQL commands

Lecture 34 Data warehouse - Slowly Changing Dimensions

Section 3: Ingest and Transform data - Lakehouse

Lecture 35 Section Code

Lecture 36 What is a Lakehouse

Lecture 37 Lab - Microsoft Fabric Lakehouse - Creating the lakehouse

Lecture 38 Lab - Microsoft Fabric Lakehouse - Ingesting data via files

Lecture 39 Microsoft Fabric Lakehouse - Delta Lake

Lecture 40 Lab - Microsoft Fabric Lakehouse - Ingesting data - Data pipeline - Data setup

Lecture 41 Lab-Microsoft Fabric Lakehouse-Ingesting data-Data pipeline-Running the pipeline

Lecture 42 Microsoft Fabric - Data pipeline - Running the pipeline based on a schedule

Lecture 43 Lab - Microsoft Fabric Lakehouse - Shortcuts - Azure Data Lake

Lecture 44 Lab - Microsoft Fabric Lakehouse - Shortcuts - AWS S3

Lecture 45 Lab - Microsoft Fabric Lakehouse - Data Pipelines use case - Overview

Lecture 46 Lab - Microsoft Fabric Lakehouse - Data Pipelines use case - Azure SQL database

Lecture 47 Lab - Microsoft Fabric Lakehouse - Data Pipelines use case - Implementation

Lecture 48 About using Apache Spark on Microsoft Fabric

Lecture 49 Lab - Microsoft Fabric - Notebooks - Loading data into a data frame

Lecture 50 Lab - Microsoft Fabric - Notebooks - Detecting NULL values

Lecture 51 Lab - Microsoft Fabric - Notebooks - Checking for duplicate rows

Lecture 52 Lab - Microsoft Fabric - Notebooks - Building the Fact table - Initial setup

Lecture 53 Lab - Microsoft Fabric - Notebooks - Building the Fact table - Implementation

Lecture 54 Lab - Microsoft Fabric - Notebooks - Extracting values

Lecture 55 Lab - Microsoft Fabric - Notebooks - Building the Dimension tables

Lecture 56 Lab - Microsoft Fabric - Running notebooks and part of a data pipeline

Lecture 57 Lab - Microsoft Fabric - Notebooks - Merging data

Section 4: Ingest and Transform data - Eventhouse

Lecture 58 Section Code

Lecture 59 Microsoft Fabric - What is an event house

Lecture 60 Lab - Microsoft Fabric - Event house - Create an event house

Lecture 61 Lab - Microsoft Fabric - Event house - Ingest sample data

Lecture 62 Lab - Microsoft Fabric - Event house - Ingest data from Azure data lake

Lecture 63 About the Kusto Query Language

Lecture 64 Microsoft Fabric - Event house - Event stream

Lecture 65 Lab - Microsoft Fabric - Event house -Event stream - Creating an Azure Event Hub

Lecture 66 Lab - Microsoft Fabric - Eventhouse - Setting up the Eventstream

Lecture 67 Lab - Microsoft Fabric - Eventhouse - Ingesting sample data into an event stream

Lecture 68 Lab - Microsoft Fabric - Eventhouse - Working with KQL queries

Lecture 69 Lab - Microsoft Fabric - Eventhouse - Creating our own data tables

Lecture 70 Lab - Microsoft Fabric - Event house - Transform data - Choose columns

Lecture 71 Lab - Microsoft Fabric - Event house - Transform data - Filter data

Lecture 72 Note - Microsoft Fabric - Eventhouse - OneLake Availability

Lecture 73 Note - Microsoft Fabric - Eventhouse - Azure SQL database - Change data capture

Lecture 74 Cleaning up our resources

Section 5: Implement and manage an analytics solution

Lecture 75 Section Code

Lecture 76 Lab - Microsoft Fabric - Creating a new workspace

Lecture 77 Lab - Microsoft Fabric - Giving admin permissions over the tenant

Lecture 78 Lab - Microsoft Fabric - Assigning users to Microsoft Fabric

Lecture 79 Lab - Microsoft Fabric - What can be the new user do

Lecture 80 Lab - Microsoft Fabric - Data warehouse - Giving access to update tables - T-SQL

Lecture 81 Lab - Microsoft Fabric - Data warehouse - Giving access to update tables - Works

Lecture 82 Lab - Microsoft Fabric - Data warehouse - Column Level security

Lecture 83 Lab - Microsoft Fabric - Data warehouse - Row-level security

Lecture 84 Microsoft Fabric - Data warehouse - Data Masking

Lecture 85 Lab - Microsoft Fabric - Data warehouse - Data Masking

Lecture 86 Microsoft Fabric - Sensitivity Labels

Lecture 87 Microsoft Fabric - Endorse items

Lecture 88 Microsoft Fabric - Domains

Lecture 89 Microsoft Fabric - Deployment pipelines

Lecture 90 Lab - Microsoft Fabric - Deployment pipelines - Deployment pipelines

Lecture 91 Lab - Microsoft Fabric - Deployment pipelines - Additional notes

Lecture 92 Microsoft Fabric - Version Control

Lecture 93 Microsoft Fabric - Example on using version control

Section 6: Monitor and optimize an analytics solution

Lecture 94 Section Code

Lecture 95 Making decisions

Lecture 96 Environments in Microsoft Fabric

Lecture 97 High concurrency mode - Notebooks

Lecture 98 Microsoft Fabric Lakehouse shortcuts - Cache

Lecture 99 Lab - Managed Private connections - Overview

Lecture 100 Lab - Managed Private connections - Implementation

Lecture 101 Admin Monitoring workspace

Lecture 102 Monitoring hub

Lecture 103 Lakehouse Table maintenance

Lecture 104 KQL Queries - Best Practices

Lecture 105 EventStream - Monitor status and performance

Lecture 106 Monitoring data pipelines

Lecture 107 Manage the connections

Lecture 108 Monitoring a data warehouse

Section 7: Practice Tests

This course is intended for learners who are aiming to become Fabric Data Engineers.,This course is intended for data enthusiasts who want to learn on how to use Microsoft Fabric for hosting data warehouses and lakehouses.