Implement CI/CD in Azure Data Factory using Azure Devops from Coursera

In this project, we are going to see how to implement CI/CD in Azure Data Factory using Azure Devops In real world scenarios, usually you would have a DEV environment and QA environment and PROD environment while implementing data engineering solutions using Azure Data Factory. Also, there would be three different Azure Data Factory services created, one for each environment (DEV,QA,PROD). So for faster and automated deployments of your data factory pipelines from one environment to another (DEV to QA, DEV to PROD) we can use Azure Devops CI/CD functionality to achieve this. Hence , in this project we are going to see with an example how to deploy Azure Data Factory metadata(pipelines/linked services/datasets etc) from DEV to QA using Azure Devops CI / CD pipelines. Pre requisites: 1. Azure subscription account(its preferred to have owner level access on the subscription account) 2. Basic understanding of Azure Data Factory 3. Azure Devops account Here is a brief description of the tasks we are going to perform in this project: Task1: Setup a DEV and QA environments In this task we are going to create a ADF account for DEV environment and a ADF account for QA environment. Also, we would be creating Azure Data Lake Storage Account for DEV and QA. Task2: Configure Azure Devops account In this task, we are going to configure the Azure Devops account by creating an organization and a project. Also, we would be creating a sample pipeline in ADF Dev environment and setup code repository in ADF Dev environment. Task3: Create Azure Devops pipeline for CI/CD In this task, we are going to create pipeline in Azure Devops which will contain the actual logic to perform CI/CD of Azure Data Factory pipelines Task4: Demo of Azure Devops CI/CD pipeline In this task, we are going to see Devops CI/CD in action. So, we would be making some changed in Dev ADF pipeline and publish it to see if those changes were automatically migrated to QA ADF service. Task5: Deploy to multiple environments In this task, we are going to see how to deploy the data factory metadata to multiple environments (DEV,PROD,UAT etc) using the Azure Devops CI/CD pipeline

Good to know

Know what's good

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Emphasizes real world tasks, such as deploying data factory pipelines to different environments, which better prepares learners for the industry

Taught by Amit Navgire, a recognized expert in data engineering and Azure Data Factory

Involves hands-on exercises, making the learning experience more interactive and engaging

Focuses on CI/CD in Azure Data Factory, which is highly relevant to DevOps practices in modern software development

Requires basic understanding of Azure Data Factory, which may be a barrier to beginners

Course materials are not provided, which may require learners to have access to additional resources

Reviews summary

Azure data factory ci/cd with azure devops

The course has received mixed reviews. One learner said that they found the course poorly organized, while another said it was well-explained. Overall, it's a good idea to review all of the notes below before making a decision about enrolling in this course.

Author has explained this in a very easy way.

"Author has explained this in a very easy way."

Not well organized

"Not well organized"

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 Implement CI/CD in Azure Data Factory using Azure Devops with these activities:

Review Azure Data Factory Fundamentals

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Review the basics of Azure Data Factory to strengthen your understanding of the concepts and terminology used in the course.

Browse courses on Azure Data Factory

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Read documentation on Azure Data Factory website
Rewatch introductory videos or tutorials on Azure Data Factory
Attend a virtual workshop or webinar on Azure Data Factory

Create Data Pipelines in Azure Data Factory

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Create sample data pipelines in Azure Data Factory to apply the concepts you learn in the course and gain hands-on practice.

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Follow along with the step-by-step instructions in the course
Try creating different types of data pipelines (e.g., data ingestion, data transformation, data analysis)
Experiment with different data sources and sinks
Troubleshoot and debug your data pipelines

Attend an Azure Data Factory Workshop

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Attend a workshop or training session focused on Azure Data Factory to enhance your knowledge and skills.

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Find upcoming workshops or training sessions
Register for the workshop
Attend the workshop
Take notes and ask questions
Apply what you learned in the workshop to your own projects

Six other activities

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Create a Resource Library for Azure Data Factory CI/CD

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Gather and organize useful resources, documentation, and examples related to Azure Data Factory CI/CD.

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Collect links to relevant documentation
Find and bookmark tutorials and blog posts
Create a folder or notebook to store the resources
Categorize and organize the resources
Share the resource library with others

Explore Azure Devops for CI/CD

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Follow online tutorials to learn how to use Azure Devops for continuous integration and continuous delivery (CI/CD) of Azure Data Factory pipelines.

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Find tutorials from Microsoft Learn or other reputable sources
Follow the step-by-step instructions in the tutorials
Set up a sample CI/CD pipeline for Azure Data Factory
Trigger a CI/CD pipeline and observe the results

Answer Questions in Azure Data Factory Forums

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Provide support to other Azure Data Factory users by answering questions in online forums.

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Join Azure Data Factory forums or communities
Browse through questions and identify those that you can answer
Write clear and concise responses
Follow up on questions to ensure understanding
Share your own knowledge and experiences

Contribute to an Open-Source Project Related to Azure Data Factory

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Identify and contribute to open-source projects that enhance Azure Data Factory or provide related functionality.

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Browse through open-source projects on GitHub or other platforms
Identify a project that aligns with your interests and skills
Read the project documentation and contribute guidelines
Propose and implement your contributions
Collaborate with other contributors

Write a Blog Post on Azure Data Factory CI/CD

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Write a blog post to summarize what you learned about Azure Data Factory CI/CD and share your experiences with others.

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Brainstorm ideas for the blog post
Write an outline for the blog post
Write the content for the blog post
Edit and proofread your blog post
Publish your blog post

Build a Data Platform using Azure Data Factory and CI/CD

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Apply your knowledge of Azure Data Factory and CI/CD to develop a comprehensive data platform that meets specific business requirements.

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Define the scope and objectives of the project
Design the data platform architecture
Implement the data platform using Azure Data Factory and CI/CD
Test and deploy the data platform
Monitor and maintain the data platform

Career center

Learners who complete Implement CI/CD in Azure Data Factory using Azure Devops will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use data to develop predictive models and make predictions about future events. This course will provide you with the skills and knowledge you need to succeed in this role, including how to use Azure Data Factory to prepare and analyze data for machine learning.

See salaries and explore the career path for Data Scientist

Data Engineer

Data Engineers create and maintain the infrastructure and systems that allow data to be collected, processed, and analyzed. This course will provide you with the skills and knowledge you need to succeed in this role, including how to use Azure Data Factory to create and manage data pipelines.

See salaries and explore the career path for Data Engineer

Machine Learning Engineer

Machine Learning Engineers build and deploy machine learning models. This course will provide you with the skills and knowledge you need to succeed in this role, including how to use Azure Data Factory to prepare and analyze data for machine learning.

See salaries and explore the career path for Machine Learning Engineer

Data Analyst

Data Analysts use data to solve business problems and make informed decisions. This course will provide you with the skills and knowledge you need to succeed in this role, including how to use Azure Data Factory to analyze data and create reports.

See salaries and explore the career path for Data Analyst

Data Warehouse Engineer

Data Warehouse Engineers design and build data warehouses. This course will provide you with the skills and knowledge you need to succeed in this role, including how to use Azure Data Factory to create and manage data pipelines that load data into a data warehouse.

See salaries and explore the career path for Data Warehouse Engineer

Software Engineer

Software Engineers design, develop, and maintain software systems. This course will provide you with the skills and knowledge you need to succeed in this role, including how to use Azure Data Factory to integrate data from different sources and create data pipelines.

See salaries and explore the career path for Software Engineer

Cloud Architect

Cloud Architects design and implement cloud computing solutions. This course will provide you with the skills and knowledge you need to succeed in this role, including how to use Azure Data Factory to create and manage data pipelines in the cloud.

See salaries and explore the career path for Cloud Architect

Business Intelligence Analyst

Business Intelligence Analysts use data to make informed decisions about business operations. This course will provide you with the skills and knowledge you need to succeed in this role, including how to use Azure Data Factory to analyze data and create reports.

See salaries and explore the career path for Business Intelligence Analyst

Data Integration Specialist

Data Integration Specialists integrate data from different sources into a single, unified system. This course will provide you with the skills and knowledge you need to succeed in this role, including how to use Azure Data Factory to create and manage data pipelines that integrate data from different sources.

See salaries and explore the career path for Data Integration Specialist

Data Quality Analyst

Data Quality Analysts ensure that data is accurate, complete, and consistent. This course will provide you with the skills and knowledge you need to succeed in this role, including how to use Azure Data Factory to create and manage data pipelines that cleanse and transform data.

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Database Administrator

Database Administrators manage and maintain databases. This course will provide you with the skills and knowledge you need to succeed in this role, including how to use Azure Data Factory to create and manage data pipelines that load data into a database.

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Data Governance Analyst

Data Governance Analysts develop and implement data governance policies and procedures. This course will provide you with the skills and knowledge you need to succeed in this role, including how to use Azure Data Factory to create and manage data pipelines that comply with data governance policies and procedures.

See salaries and explore the career path for Data Governance Analyst

Data Visualization Analyst

Data Visualization Analysts use data to create visualizations that communicate insights to stakeholders. This course will provide you with the skills and knowledge you need to succeed in this role, including how to use Azure Data Factory to create and manage data pipelines that extract and prepare data for visualization.

See salaries and explore the career path for Data Visualization Analyst

Systems Engineer

Systems Engineers design, implement, and maintain computer systems. This course will provide you with the skills and knowledge you need to succeed in this role, including how to use Azure Data Factory to create and manage data pipelines that integrate data from different sources.

See salaries and explore the career path for Systems Engineer

DevOps Engineer

DevOps Engineers implement and maintain DevOps practices and tools. This course will provide you with the skills and knowledge you need to succeed in this role, including how to use Azure Data Factory to create and manage data pipelines that are deployed and managed using DevOps practices.

See salaries and explore the career path for DevOps Engineer

Implement CI/CD in Azure Data Factory using Azure Devops

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Azure data factory ci/cd with azure devops

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