Azure Data Factory In 2 Hours - Practical Hands On Lab

Name: Azure Data Factory In 2 Hours - Practical Hands On Lab
Rating: 4.5 (24 reviews)

Quick jumpstart to Azure Data Factory with practical lab sessions

Highest Rated

Created byAmit Navgire

Last updated 5/2024

English

English [Auto],

What you'll learn

Learn how to create ETL pipelines in Azure Data Factory
Basics of Azure Data Lake Gen2 and Azure SQL DB
Learn how to load data from Azure Data Lake to Azure SQL DB
Learn how to load data from on premise file system to Azure SQL DB
Learn how to transform data using dataflow activity
Learn how to monitor pipelines and debug error

Course content

1 section • 13 lectures • 2h 26m total length

Create Azure Data Factory Service in Azure4:14
Create an Azure Data Factory service in the Azure portal, configure a data lake and SQL database, and organize resources in a resource group with region and v2 settings.
Tour of ADF Service7:38
Explore the Azure Data Factory interface, launch the Data Factory Studio, and author pipelines with drag-and-drop activities, configuring steps like get metadata, execute SS packages, and if condition.
Create Azure Data Lake Storage Gen210:42
Create and configure an Azure data lake storage Gen2 account, enable hierarchical namespace, select redundancy, and use blob containers to organize data for scalable, cost-effective storage.
Create Azure SQL DB6:16
Create an Azure SQL database for data factory pipelines by provisioning a new SQL server, configuring firewall, and testing via the query editor.
Copy Activity - ADLS to SQL DB29:26
Create a hello world pipeline to copy data from Azure data lake Gen2 to Azure SQL database using copy data activity, with reusable linked services and data sets.
Self Hosted IR & Copy From Onprem to SQL DB20:45
Install and register the self-hosted integration runtime in Azure Data Factory, using a dedicated gateway machine to access on premise sources, and copy data from emp.csv to Azure SQL database.
Lookup Activity9:29
Use the lookup activity in Azure Data Factory to read data from a data set or file. Query tables, execute stored procedures, and view outputs to feed subsequent pipeline steps.
Get Metadata Activity7:37
Learn how the get metadata activity in Azure Data Factory retrieves object metadata for folders and tables, including child items and column structure, guiding dataset configuration and downstream pipeline use.
Dataflow - Source Transformation13:17
learn how to build a data flow in Azure Data Factory for row-by-row transformations, using sources, inline datasets, and a spark cluster.
Dataflow - Join Transformation9:35
Explore how to perform a two-source join in Azure Data Factory data flow, connecting employee and department CSV sources, validating results with data preview in debug mode.
Dataflow - Select & Sort Transformation3:28
Explore select and sort transformations to clean and organize data: remove duplicate columns, rename fields to employee name, salary, and department, and sort by salary after converting it to integer.
Dataflow - Sink Transformation8:09
Explore the sink transformation in a data flow by loading data into an Azure SQL database table, configuring inserts, mapping fields, and handling errors with pre/post scripts and schema drift.
Introduction to Parameters16:00
Master parameters in Azure Data Factory to enable dynamic behavior across pipelines, including global, pipeline, data set, data flow, and linked service parameters, and use dynamic content to pass values.

Requirements

Basic understanding of Azure or cloud
Students should have an Azure subscription

Description

Welcome to our accelerated course on Azure Data Factory!

Embark on a rapid journey to Azure Data Factory mastery with our intensive two-hour workshop. Designed for busy professionals who crave efficient yet comprehensive learning experiences, this course offers a streamlined introduction to Azure Data Factory, Azure Data Lake Gen2, and Azure SQL DB, all within a condensed timeframe.

Say goodbye to lengthy courses and hello to hands-on, practical learning!

In today's fast-paced data landscape, agility is paramount. Our workshop prioritizes practical, hands-on learning, ensuring that you acquire the skills you need to architect and execute data pipelines swiftly and effectively. By immersing yourself in our lab sessions, you'll navigate real-world scenarios, honing your abilities to orchestrate seamless data integration and transformation processes.

This workshop is tailored for individuals seeking a quick yet robust understanding of Azure Data Factory's capabilities. Whether you're a seasoned data professional looking to expand your toolkit or a newcomer eager to jumpstart your career in data engineering, our accelerated approach empowers you to hit the ground running.

Throughout the course, you'll explore the intricacies of Azure Data Factory, mastering its features for data movement, transformation, and orchestration. You'll harness the power of Azure Data Lake Gen2 and Azure SQL DB, leveraging their capabilities to build end-to-end data pipelines that drive actionable insights.

At the heart of our workshop lies a commitment to practical skill-building. Guided by expert instructors, you'll tackle hands-on exercises that simulate real-world challenges, cementing your understanding of Azure Data Factory's core concepts and functionalities. By the end of the workshop, you'll emerge equipped with the knowledge and confidence to tackle data engineering projects head-on.

Don't let time constraints hinder your learning journey. Join us for an intensive two-hour workshop and unlock the full potential of Azure Data Factory in record time. Get ready to accelerate your data engineering aspirations and propel your career forward with Azure Data Factory Mastery!

Who this course is for:

University students who aspire to become azure data engineer
IT professionals who needs a quick jumpstart in their Azure Data Engineer journey
Folks who wants a quick introduction to Azure Data Factory in just 2 hours