Data Integration with Microsoft Azure Data Factory from Coursera

In this course, you will learn how to create and manage data pipelines in the cloud using Azure Data Factory.

This course is part of a Specialization intended for Data engineers and developers who want to demonstrate their expertise in designing and implementing data solutions that use Microsoft Azure data services. It is ideal for anyone interested in preparing for the DP-203: Data Engineering on Microsoft Azure exam (beta).

This is the third course in a program of 10 courses to help prepare you to take the exam so that you can have expertise in designing and implementing data solutions that use Microsoft Azure data services. The Data Engineering on Microsoft Azure exam is an opportunity to prove knowledge expertise in integrating, transforming, and consolidating data from various structured and unstructured data systems into structures that are suitable for building analytics solutions that use Microsoft Azure data services. Each course teaches you the concepts and skills that are measured by the exam.

By the end of this Specialization, you will be ready to take and sign-up for the Exam DP-203: Data Engineering on Microsoft Azure (beta).

What's inside

Syllabus

Integrate data with Azure Data Factory or Azure Synapse Pipeline

Describe the core components of Azure Data Factory that enable you to create large scale data ingestion solutions in the cloud

Traffic lights

Read about what's good

what should give you pause

and possible dealbreakers

Builds a foundation for and develops data engineering expertise using Microsoft Azure data services

Designed for data engineers and developers who want to master Microsoft Azure data services

Knowledge gained from the course is testable via the DP-203: Data Engineering on Microsoft Azure exam (beta)

Taught by Microsoft, a leading innovator in cloud computing

Reviews summary

Azure data factory: dp-203 exam prep

According to students, this course is a highly valuable resource for mastering Azure Data Factory and preparing for the DP-203 exam. Learners consistently praise the instructor's clear, engaging, and knowledgeable delivery, which helps simplify complex topics. The course offers practical, hands-on labs that significantly enhance understanding and provide a strong foundation for real-world data engineering tasks. While many find the material very up-to-date, a few recent reviews still note minor issues with outdated resource names or Azure portal UI alignment, which may require some troubleshooting. It's ideal for those with some prior Azure exposure, though complete beginners might face initial challenges with lab setups.

Benefits learners with existing Azure knowledge; beginners may struggle.

"I came in with some ADF experience, and this course helped me fill in gaps and understand best practices."

"Not ideal for complete beginners unless you're very patient."

"I did find some of the lab setups a bit confusing at times, especially if you're not already familiar with other Azure services."

Practical labs reinforce concepts, but some minor setup issues.

"The hands-on labs, which were extremely helpful for solidifying my understanding."

"The labs are fantastic, really cementing the concepts."

"The labs are good, but I encountered a few minor issues with outdated resource names that needed slight adjustments on my end."

Excellent for DP-203 exam prep and real-world data engineering.

"The material is very up-to-date and directly applicable to the DP-203 exam."

"This course provides a strong foundation for real-world data engineering tasks and significantly boosted my confidence for the DP-203."

"This course is a must-take for anyone serious about Azure Data Factory and passing the DP-203 exam."

Instructor provides clear, engaging, and knowledgeable explanations.

"The instructor, Mark, does an incredible job of explaining complex topics in a clear and concise manner."

"The content is well-structured, and the instructor's delivery is engaging."

"The instructor is knowledgeable and makes learning enjoyable. The pace is just right..."

Some course materials and UI references are outdated, causing frustration.

"Some of the labs and demos don't perfectly align with the current Azure portal UI, which caused some frustration and troubleshooting."

"The labs were frustrating due to outdated UI references and broken links for sample data. I spent more time troubleshooting than learning."

"A common issue was the outdated Azure portal screenshots and some deprecated features mentioned. It would be great if these were updated."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Integration with Microsoft Azure Data Factory with these activities:

Compile and organize course materials

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Stay organized and improve your retention by compiling and reviewing course materials.

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Create a central repository for notes, assignments, and other materials
Organize materials by topic or module
Review materials regularly

Review basic programming concepts

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Strengthen your foundation in programming concepts to enhance your Data Factory skills.

Browse courses on Programming

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Review online tutorials or books on basic programming
Practice solving coding challenges on platforms like LeetCode or HackerRank

Review cloud computing concepts

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Refresh your knowledge of cloud computing concepts to enhance your understanding of Data Factory.

Browse courses on Cloud Computing

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Review online courses or tutorials on cloud computing
Practice using cloud services through hands-on exercises

Seven other activities

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Follow guided tutorials on Data Factory features

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Expand your knowledge of Data Factory features by following guided tutorials.

Browse courses on Azure Data Factory

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Find tutorials on Microsoft Learn or YouTube
Choose a tutorial that covers a feature you want to learn
Follow the tutorial step-by-step

Practice Data Factory concepts with hands-on exercises

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Solidify your understanding of Azure Data Factory concepts through practical exercises.

Browse courses on Azure Data Factory

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Set up your Azure Data Factory environment
Create a data pipeline to ingest data from a source
Transform data using data flow activities
Orchestrate data movement and transformation

Practice transforming data using Azure Data Factory Data Flows

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Practice data transformation tasks to become more proficient in using Azure Data Factory Data Flows.

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Create a new data flow in Azure Data Factory
Add a source dataset to the data flow
Add a transformation to the data flow to perform data transformations
Add a sink dataset to the data flow to store the transformed data
Publish the data flow and trigger a run

Practice Azure Data Factory transformations

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Reinforce your understanding of data transformations in Azure Data Factory by completing practice exercises and drills.

Browse courses on Data Transformation

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Review the Azure Data Factory documentation on transformations.
Complete the hands-on labs in the Azure Data Factory learning module on transformations.
Create your own data transformation pipelines using Azure Data Factory.

Join a study group or online forum for Data Factory

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Engage with other learners and experts to discuss Data Factory concepts and share knowledge.

Browse courses on Azure Data Factory

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Find a study group or online forum
Join the group and participate in discussions
Share your knowledge and learn from others

Build a data pipeline using Data Factory

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Apply your skills by creating a data pipeline that meets a specific business need.

Browse courses on Azure Data Factory

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Define the data sources and destination
Design the data pipeline architecture
Implement the pipeline using Data Factory activities
Test and deploy the pipeline

Participate in data science competitions or hackathons

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Challenge yourself and showcase your skills by participating in data science competitions or hackathons.

Browse courses on Data Science

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Find a competition or hackathon that aligns with your interests
Form a team or work individually
Develop a solution using Data Factory
Submit your solution and compete for prizes or recognition

Career center

Learners who complete Data Integration with Microsoft Azure Data Factory will develop knowledge and skills that may be useful to these careers:

Data Engineer

A Data Engineer designs and builds the systems and processes that manage and transform data. They ensure that the data is reliable, secure, and accessible to those who need it. This course teaches the skills required for building effective data engineering solutions using Azure Data Factory.

See salaries and explore the career path for Data Engineer

Data Architect

A Data Architect is an architect who designs and oversees the implementation of data management systems. The systems that they design and oversee provide secure, reliable, efficient, and integrated access to data. They may oversee data integration projects which would require them to be familiar with integration techniques and solutions such as the ones taught in this course.

See salaries and explore the career path for Data Architect

Database Architect

A Database Architect designs and manages the structure and organization of databases. They ensure that databases are efficient, scalable, and secure. This course provides a foundation in data integration and data transformation, which are essential skills for Database Architects.

See salaries and explore the career path for Database Architect

Data Analyst

Data Analysts collect, clean, and analyze data to identify trends and patterns. They use this information to make recommendations and improve decision-making. This course provides a foundation in data integration and data transformation, which are essential skills for Data Analysts.

See salaries and explore the career path for Data Analyst

Database Administrator

A Database Administrator (DBA) is responsible for the day-to-day operation and maintenance of databases. They ensure that databases are running smoothly and efficiently. This course provides a foundation in data integration and data transformation, which are essential skills for DBAs.

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Software Engineer

A Software Engineer designs, develops, and maintains software applications. They may work on projects that involve data integration and data transformation. This course provides a foundation in data integration and data transformation, which are essential skills for Software Engineers.

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Information Architect

An Information Architect designs and manages the organization and structure of information systems. They ensure that information is accessible, usable, and relevant to the needs of users. This course provides a foundation in data integration and data transformation, which are essential skills for Information Architects.

See salaries and explore the career path for Information Architect

Business Intelligence Analyst

A Business Intelligence Analyst analyzes data to identify trends and patterns that can help businesses make better decisions. They may work on projects that involve data integration and data transformation. This course provides a foundation in data integration and data transformation, which are essential skills for Business Intelligence Analysts.

See salaries and explore the career path for Business Intelligence Analyst

Data Scientist

A Data Scientist uses scientific methods to extract knowledge from data. They may work on projects that involve data integration and data transformation. This course provides a foundation in data integration and data transformation, which are essential skills for Data Scientists.

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Machine Learning Engineer

A Machine Learning Engineer develops and deploys machine learning models. They may work on projects that involve data integration and data transformation. This course provides a foundation in data integration and data transformation, which are essential skills for Machine Learning Engineers.

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Cloud Engineer

A Cloud Engineer designs and manages cloud computing systems. They may work on projects that involve data integration and data transformation. This course provides a foundation in data integration and data transformation, which are essential skills for Cloud Engineers.

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Systems Analyst

A Systems Analyst analyzes and designs computer systems. They may work on projects that involve data integration and data transformation. This course provides a foundation in data integration and data transformation, which are essential skills for Systems Analysts.

See salaries and explore the career path for Systems Analyst

Project Manager

A Project Manager plans, executes, and closes projects. They may work on projects that involve data integration and data transformation. This course provides a foundation in data integration and data transformation, which are essential skills for Project Managers.

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Technical Writer

A Technical Writer creates and maintains technical documentation. They may work on projects that involve data integration and data transformation. This course provides a foundation in data integration and data transformation, which are essential skills for Technical Writers.

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Data Librarian

A Data Librarian organizes and manages data. They may work on projects that involve data integration and data transformation. This course provides a foundation in data integration and data transformation, which are essential skills for Data Librarians.

See salaries and explore the career path for Data Librarian