CF

Azure Data Engineer Workshop In A Weekend

9h 18m 40s
English
Paid

Azure Data Engineer Workshop In A Weekend is a 29-lesson 9 hours 18 minutes self-paced course by Udemy. Get a quick jumpstart in your journey of Azure Data Engineer.

Course facts

Lessons
29
Duration
9 hours 18 minutes
Level
All levels
Language
English
Updated
Instructor
Udemy
Price
Premium
Get a quick jumpstart in your journey of Azure Data Engineer.Create ETL pipelines using Data Factory, Data Lake & SQL DB.

Why Take This AMAZING Course?

  • Highest Rated Instructor Here On Udemy For Azure

  • Learn From A Professional Who Works as Azure Data Architect and Has Taught More Than 40,000 Students.

  • THE MOST UPDATE AND MODERN TUTORIAL. Dont Settle For Outdated Content!

  • Focus of this course is to provide a quick jumpstart in your journey of Azure Data Engineer.

  • The most popular part of the course is it contains 100% practical hands on lab sessions and minimal theory.

  • In this course, you are going to learn the most important technologies required for Azure Data Engineer like Azure Data Lake Gen2, Azure SQL DB, Azure Data Factory etc.

  • If you are planning for Azure Data Engineer certification (DP-203) then this course will provide a good foundation


Who teaches Azure Data Engineer Workshop In A Weekend? Udemy

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Udemy is the largest open marketplace for online courses on the internet. Founded in 2010 by Eren Bali, Oktay Caglar, and Gagan Biyani and headquartered in San Francisco, the company went public on the Nasdaq in 2021 under the ticker UDMY. The platform hosts well over two hundred thousand courses across software development, IT and cloud, data science, design, business, marketing, and creative skills, taught by tens of thousands of independent instructors. Roughly seventy million learners use it worldwide, and the corporate arm — Udemy Business — supplies a curated subset of that catalog to enterprise customers.

Because Udemy is a marketplace rather than a single editorial publisher, the catalog is uneven by design. The strongest material lives in the long-form, project-based courses authored by working engineers — full-stack JavaScript, React, Node.js, Python data science, AWS, Docker and Kubernetes, mobile development with Flutter and React Native, and cloud certification preparation. The CourseFlix listing under this source is the slice of that catalog that has been mirrored here for offline-friendly viewing, organized by topic and updated as new releases land. Pricing on Udemy itself swings dramatically with the site's near-permanent sales, which is why the platform is best treated as a deep reference catalog: pick instructors with strong reviews and a track record of updating their material rather than buying on the headline price alone.

What lessons are included in Azure Data Engineer Workshop In A Weekend?

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#1: Fundamentals of cloud computing
All Course Lessons (29)
#Lesson TitleDurationAccess
1
Fundamentals of cloud computing Demo
31:28
2
Create FREE Azure account
11:47
3
What is Azure Data Factory?
04:32
4
Lab:Create Azure Data Factory
12:39
5
Lab: Building blocks of Azure Data Factory
53:07
6
Lab: Copy Data - Scenario 1
54:43
7
Lab: Copy Data - Scenario 2
30:15
8
Lab: Lookup Activity
09:12
9
Lab: GetMetadata Activity
09:55
10
Lab: Filter Activity
14:20
11
Lab: Foreach Loop
12:11
12
Lab: If condition Activity
15:40
13
Lab: Execute Pipeline Activity
01:53
14
Dataflow Overview
10:33
15
Lab: Source
24:53
16
Lab: Join
10:26
17
Lab: Select & Sort
10:33
18
Lab: Exists
09:05
19
Lab: Derived Column
18:43
20
Lab: Filter
04:44
21
Lab: Aggregate
10:20
22
Lab: Conditional Split
09:59
23
Lab: New Branch
05:09
24
Lab: Sink & Alter
36:09
25
Lab: Parameters
49:23
26
Theory: Incremental Data Load
16:10
27
Lab: Incremental Data Load
45:03
28
Theory: Slowly Changing Dimension
09:26
29
Lab: Slowly Changing Dimension
26:22
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Frequently asked questions

What are the prerequisites for enrolling in this Azure Data Engineer course?
The course does not explicitly list prerequisites, but a basic understanding of cloud computing is likely beneficial, as it covers fundamentals of cloud computing early in the lessons. Familiarity with data processing concepts and SQL may also help, given the focus on Azure Data Factory and SQL Database.
What will I be able to build by the end of this course?
By the end of the course, you will be able to create ETL pipelines using Azure Data Factory, Data Lake, and SQL Database. You will have hands-on experience through labs that cover activities like copying data, using lookup and filter activities, implementing foreach loops, and executing pipelines, among others.
Who is the intended audience for this Azure Data Engineer course?
The course is designed for individuals looking to quickly jumpstart their career as an Azure Data Engineer. It is suitable for beginners who wish to gain practical skills in building ETL pipelines using Azure tools, as well as for professionals seeking to enhance their data engineering capabilities on the Azure platform.
How does the depth of this course compare to other data engineering courses?
This course provides a focused, hands-on approach to learning Azure Data Factory and related tools in a short timeframe. It emphasizes practical labs and exercises, which may offer less depth but more immediate applicable skills compared to more comprehensive courses that cover broader data engineering techniques and theories.
What specific tools or platforms are covered in this course?
The course covers Azure Data Factory as the primary tool for building ETL pipelines. It also involves creating a free Azure account and uses Azure Data Lake and SQL Database as part of the data engineering workflow. Key activities and concepts like data flow, conditional splits, and incremental data load are also explored.
What topics are not covered in this course?
This course does not cover topics outside of Azure Data Factory, Data Lake, and SQL Database. Advanced data engineering topics, such as machine learning integrations, big data processing with services like Azure Databricks, or comprehensive data governance strategies, are not included.
What is the expected time commitment for completing this course?
The course is designed to be completed over a weekend, suggesting a time commitment of approximately two full days. With 29 lessons, including numerous labs and hands-on activities, students should be prepared to dedicate focused time to fully engage with and practice the material.