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Amit Navgire
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...
Read more
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...
Read more
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
Register for this course and see more details by visiting:
OpenCourser.com/course/qcktpq/implement
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
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
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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
Show steps
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
Show steps
-
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
Show steps
Create sample data pipelines in Azure Data Factory to apply the concepts you learn in the course and gain hands-on practice.
Show steps
-
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
Show steps
Attend a workshop or training session focused on Azure Data Factory to enhance your knowledge and skills.
Show steps
-
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
Expand to see all activities and additional details
Show all nine activities
Create a Resource Library for Azure Data Factory CI/CD
Show steps
Gather and organize useful resources, documentation, and examples related to Azure Data Factory CI/CD.
Show steps
-
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
Show steps
Follow online tutorials to learn how to use Azure Devops for continuous integration and continuous delivery (CI/CD) of Azure Data Factory pipelines.
Show steps
-
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
Show steps
Provide support to other Azure Data Factory users by answering questions in online forums.
Show steps
-
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
Show steps
Identify and contribute to open-source projects that enhance Azure Data Factory or provide related functionality.
Show steps
-
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
Show steps
Write a blog post to summarize what you learned about Azure Data Factory CI/CD and share your experiences with others.
Show steps
-
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
Show steps
Apply your knowledge of Azure Data Factory and CI/CD to develop a comprehensive data platform that meets specific business requirements.
Show steps
-
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
Review Azure Data Factory Fundamentals
Show steps
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
Show steps
Show steps
Show steps
- 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
Show steps
Create sample data pipelines in Azure Data Factory to apply the concepts you learn in the course and gain hands-on practice.
Show steps
Show steps
Show steps
- 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
Show steps
Attend a workshop or training session focused on Azure Data Factory to enhance your knowledge and skills.
Show steps
Show steps
Show steps
- 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
Expand to see all activities and additional details
Show all nine activities
Create a Resource Library for Azure Data Factory CI/CD
Show steps
Gather and organize useful resources, documentation, and examples related to Azure Data Factory CI/CD.
Show steps
Show steps
Show steps
- 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
Show steps
Follow online tutorials to learn how to use Azure Devops for continuous integration and continuous delivery (CI/CD) of Azure Data Factory pipelines.
Show steps
Show steps
Show steps
- 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
Show steps
Provide support to other Azure Data Factory users by answering questions in online forums.
Show steps
Show steps
Show steps
- 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
Show steps
Identify and contribute to open-source projects that enhance Azure Data Factory or provide related functionality.
Show steps
Show steps
Show steps
- 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
Show steps
Write a blog post to summarize what you learned about Azure Data Factory CI/CD and share your experiences with others.
Show steps
Show steps
Show steps
- 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
Show steps
Apply your knowledge of Azure Data Factory and CI/CD to develop a comprehensive data platform that meets specific business requirements.
Show steps
Show steps
Show steps
- 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 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.
Data Engineer
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.
Machine Learning 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.
Data Analyst
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.
Data Warehouse Engineer
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.
Software 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.
Cloud Architect
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.
Business Intelligence Analyst
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.
Data Integration Specialist
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.
Data Quality Analyst
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.
Database Administrator
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.
Data Governance Analyst
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.
Data Visualization 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.
Systems Engineer
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.
DevOps 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.
For more career information including salaries, visit:
OpenCourser.com/course/qcktpq/implement
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Implement CI/CD in Azure Data Factory using Azure Devops.
Save
Provides a comprehensive overview of DevOps principles and practices. It would help learners who are looking to learn more about DevOps and how to implement it in their own organizations.
Save
Provides a fictionalized account of the challenges of implementing DevOps in a large organization. It valuable resource for anyone who wants to learn more about the challenges of DevOps or how to overcome them.
Provides a comprehensive guide to data warehouse design and implementation. It would help learners who are looking to develop a deeper understanding of data warehouse design and its application in real-world scenarios.
Save
Provides a detailed account of the DevOps journey at Allstate, one of the largest insurance companies in the world. It valuable resource for anyone who wants to learn more about how DevOps can be implemented in a large organization.
Provides a comprehensive introduction to Azure DevOps, covering its key features and capabilities. It would help learners who are new to Azure DevOps quickly get up to speed.
Provides a comprehensive overview of the Lean Startup methodology, which process for developing and validating new products and services. It valuable resource for anyone who wants to learn more about the Lean Startup methodology or use it in their work.
Provides a gentle introduction to Azure Data Factory, covering the key concepts and features of the service. It good resource for anyone who wants to learn more about Azure Data Factory or getting started using it. This book is helpful especially for beginners.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/qcktpq/implement
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Amit Navgire
Good to know
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
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