DP-203 Data Engineering on Microsoft Azure

DP-203 – Data Engineering on Microsoft Azure, available at $109.99, has an average rating of 4.52, with 313 lectures, 8 quizzes, based on 11320 reviews, and has 76714 subscribers.

You will learn about Students will be better prepared for the DP-203 certification exam Students will learn the various Azure services that pertain to Data Engineering This course is ideal for individuals who are Those who want to pursue the Microsoft Certified: Azure Data Engineer Associate or Those who want to pass the DP-203 Certification exam It is particularly useful for Those who want to pursue the Microsoft Certified: Azure Data Engineer Associate or Those who want to pass the DP-203 Certification exam.

Enroll now: DP-203 – Data Engineering on Microsoft Azure

Summary

Title: DP-203 – Data Engineering on Microsoft Azure

Price: $109.99

Average Rating: 4.52

Number of Lectures: 313

Number of Quizzes: 8

Number of Published Lectures: 278

Number of Published Quizzes: 8

Number of Curriculum Items: 321

Number of Published Curriculum Objects: 286

Number of Practice Tests: 2

Number of Published Practice Tests: 2

Original Price: $129.99

Quality Status: approved

Status: Live

What You Will Learn

Students will be better prepared for the DP-203 certification exam

Students will learn the various Azure services that pertain to Data Engineering

Who Should Attend

Those who want to pursue the Microsoft Certified: Azure Data Engineer Associate

Those who want to pass the DP-203 Certification exam

Target Audiences

Those who want to pursue the Microsoft Certified: Azure Data Engineer Associate

Those who want to pass the DP-203 Certification exam

Release v3.0 – May 2024

The entire course has been updated and refreshed. All chapters have been re-recorded. This has been done to ensure that all contents now reflect the most recent changes to the services on the Azure platform.

All course contents have also been aligned as per any changes to the course objectives.

Release v2.0 – May 2023

The entire course has been updated and refreshed. All chapters have been re-recorded. This has been done to ensure that all contents now reflect the most recent changes to the services on the Azure platform.

All course contents have also been aligned as per any changes to the course objectives.

Additional questions have been also added to the Practice Tests.

Release v1.0 Initial Release

This course is designed for students who want to attain the “Microsoft Certified: Azure Data Engineer Associate” certification

This course has contents for the Exam DP-203

The objectives covered in this course are

Design and implement data storage (40-45%)

Design and develop data processing (25-30%)

Design and implement data security (10-15%)

Monitor and optimize data storage and data processing (10-15%)

In this course students will learn about the various Azure services that pertain to Data Engineering. Some of the important aspects that students will learn include the following

What is the purpose of an Azure Data Lake Gen 2 storage account

Basics on Transact-SQL commands

How to work with Azure Synapse. This will include building a data warehouse into a dedicated SQL Pool.

How to build an ETL pipeline with the help of Azure Data Factory. There will be various scenarios on how to create mapping data flows.

How to stream data with the use of Azure Stream Analytics. You can see how SQL commands can be used for your streaming data.

Basics on the Scala programming language, and SPARK

How to work with SPARK, Scala in Azure Databricks. We will see how to work with Notebooks. We will also see how to stream data into Azure Databricks.

The different security measures and monitoring aspects to consider when working with Azure services

Course Curriculum

Chapter 1: UPDATED – Introduction

Lecture 1: IMPORTANT – How we are going to approach the exam objectives

Lecture 2: Cloud Computing

Lecture 3: Introduction to Cloud Computing

Lecture 4: Introduction to Azure

Lecture 5: The Azure Free Account

Lecture 6: Creating an Azure Free Account

Lecture 7: Tour around the Azure Portal

Lecture 8: Disabling security defaults

Lecture 9: PDF Resources Download

Chapter 2: UPDATED – Design and implement data storage – Basics

Lecture 1: Understanding Data

Lecture 2: The different data formats

Lecture 3: We need different types of storage services

Lecture 4: Lab – Creating an Azure Storage Account

Lecture 5: Lab – Working with the Azure Storage account

Lecture 6: Example of an application accessing data

Lecture 7: Example of an application accessing data – Resources

Lecture 8: Thoughts on Udemy storing data

Lecture 9: The Azure Data Lake Gen2 storage account

Lecture 10: Lab – Azure Data Lake Gen-2 storage accounts

Lecture 11: Lab – Uploading data to Azure Data Lake Gen2

Lecture 12: Getting PowerBI

Lecture 13: Using PowerBI to view your data

Chapter 3: UPDATED – Design and implement data storage – Overview on Transact-SQL

Lecture 1: Code for this section

Lecture 2: Section Introduction

Lecture 3: The Azure SQL database service

Lecture 4: Lab – Setting up a new Azure SQL database

Lecture 5: Lab – Installing Azure Data Studio

Lecture 6: Lab – Using Azure Data Studio on macOS

Lecture 7: Lab – T-SQL – SELECT clause

Lecture 8: Lab – T-SQL – WHERE clause

Lecture 9: Lab – T-SQL – ORDER BY clause

Lecture 10: Lab – T-SQL – Aggregate Functions

Lecture 11: Lab – T-SQL – GROUP BY clause

Lecture 12: Lab – Using PARTITION BY

Lecture 13: Lab – LEAD and LAG functions

Lecture 14: Lab – WITH Clause

Lecture 15: Lab – T-SQL – Create Table command

Lecture 16: Lab – T-SQL – Foreign Key constraints

Chapter 4: UPDATED – Design and implement data storage – Azure Synapse Analytics

Lecture 1: Code for this section

Lecture 2: Section Introduction

Lecture 3: A quick view on the costing aspect when using Azure Synapse

Lecture 4: What have we seen so far

Lecture 5: A data warehouse

Lecture 6: Welcome to Azure Synapse Analytics

Lecture 7: Lab – Lets create a Azure Synapse workspace

Lecture 8: About the serverless SQL pool

Lecture 9: Lets open up some data

Lecture 10: Quick note on Microsoft Entra ID and permissions

Lecture 11: Lab – Using External tables – CSV – Part 1

Lecture 12: Lab – Using External tables – CSV – Part 2

Lecture 13: Lab – External Tables – Parquet file

Lecture 14: Lab – External Tables – Multiple Parquet files

Lecture 15: Lab – OPENROWSET – JSON files

Lecture 16: Using the dedicated SQL pool

Lecture 17: The dedicated SQL pool

Lecture 18: Lab – Creating a SQL pool

Lecture 19: Lab – SQL Pool – External Tables – CSV

Lecture 20: Lab – SQL Pool – External Tables – Parquet

Lecture 21: Lab – External table – Hidden files and folders

Lecture 22: Pausing the SQL Pool

Lecture 23: Lab – Loading data into a SQL pool using Polybase

Lecture 24: Lab – Loading data into a table – COPY Command – CSV

Lecture 25: Lab – Loading data into a table – COPY Command – Parquet

Lecture 26: Lab – Loading data – Pipelines – Storage accounts

Lecture 27: Lab – Loading data – Pipelines – Azure SQL database

Lecture 28: Designing a data warehouse

Lecture 29: Fact and Dimension Tables

Lecture 30: Lab – Building a Fact Table

Lecture 31: Lab – Building a dimension table

Lecture 32: Lab – Transfer data to our SQL Pool

Lecture 33: Lab – Using Power BI for Star Schema

Lecture 34: Understanding Azure Synapse Architecture

Lecture 35: Understanding table types

Lecture 36: Lab – Creating Hash-distributed Tables

Lecture 37: Lab – Creating Replicated Tables

Lecture 38: Fact as Hash and Dimensions as Replicate

Lecture 39: More on designing tables

Lecture 40: Lab – Surrogate keys for dimension tables

Lecture 41: Slowly Changing dimensions

Lecture 42: Indexes in Azure Synapse

Lecture 43: Which Load Method to use

Lecture 44: Partitions in Azure Synapse

Lecture 45: Lab – Creating a table with partitions

Lecture 46: Lab – Switching partitions

Lecture 47: Lab – CASE statement

Lecture 48: What about the Spark Pool

Chapter 5: UPDATED – Design and Develop Data Processing – Azure Data Factory

Lecture 1: Section Introduction

Lecture 2: Code for this section

Lecture 3: Costing aspect when it comes to Azure Data Factory

Lecture 4: Extract, Transform and Load

Lecture 5: What is Azure Data Factory

Lecture 6: Starting with Azure Data Factory

Lecture 7: Lab – Azure Data Lake to Azure Synapse

Lecture 8: Lab – Generating a Parquet file

Instructors

Alan Rodrigues
Software Engineering Evangelist

Rating Distribution

1 stars: 110 votes

2 stars: 152 votes

3 stars: 817 votes

4 stars: 4158 votes

5 stars: 6087 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!