Data Integration with Microsoft Azure Data Factory

Go to Course: https://www.coursera.org/learn/azure-data-factory-data-integration

Introduction

### Course Review: Data Integration with Microsoft Azure Data Factory **Overview:** The course titled **Data Integration with Microsoft Azure Data Factory** is an exceptional offering on Coursera, aimed at data engineers and developers seeking to harness the power of Azure Data Factory for creating and managing cloud-based data pipelines. This course forms part of a broader specialization designed to equip learners with the skills necessary to effectively implement data solutions using Microsoft Azure data services. It's particularly beneficial for individuals preparing for the DP-203: Data Engineering on Microsoft Azure certification exam (currently in beta). **Course Structure and Syllabus:** The course consists of several modules, each focusing on critical components of data integration and orchestration. Below is a brief overview of the course syllabus: 1. **Integrate Data with Azure Data Factory or Azure Synapse Pipeline:** - Learn about the core components that enable the creation of large-scale cloud data ingestion solutions. 2. **Petabyte-scale Ingestion:** - Explore various methods to ingest data across different data stores, showcasing Azure Data Factory’s potential for handling large volumes. 3. **Perform Code-Free Transformation:** - Discover how to perform data transformations and cleansing without writing code, including implementing Slowly Changing Dimensions. 4. **Orchestrate Data Movement and Transformation:** - Learn to orchestrate substantial data flows using Azure Data Factory in conjunction with other Azure data services and ML technologies. 5. **Execute SSIS Packages:** - Understand how to seamlessly integrate existing SQL Server Integration Services packages into Azure Data Factory for enhanced functionality. 6. **Operationalize Your Data Factory:** - Gain insights on publishing Azure Data Factory projects between different environments, reinforcing best practices for development and deployment. 7. **Receive Data with Azure Data Share:** - Learn about ingesting data from Azure Data Share into Azure Data Factory pipelines, focusing on creating automated ingestion processes. 8. **Course Practice Exam:** - Take advantage of a practice exam to evaluate your understanding of data integration at scale using Azure Data Factory. **Why You Should Take This Course:** This course stands out for several reasons: - **Hands-On Learning:** The course emphasizes practical knowledge, encouraging learners to engage with real-world scenarios and apply their skills in a controlled environment. - **Expert Instruction:** Taught by industry professionals with advanced knowledge in Azure technologies, you can expect to receive insights that are both theoretical and practical. - **Comprehensive Curriculum:** Covering essential skills required for data integration and management within Azure, the course prepares you well for both practical implementation and theoretical exams, including the DP-203. - **Flexible Learning Pace:** Coursera's platform allows you to learn at your own pace, facilitating a personalized learning experience that can adapt to various schedules. - **Networking Opportunities:** Engaging with peers in discussion forums and group assignments provides networking opportunities and insights from a diverse set of learners. **Conclusion:** In conclusion, the **Data Integration with Microsoft Azure Data Factory** course is a valuable resource for anyone looking to deepen their understanding of cloud data solutions using Microsoft Azure. Whether you're just starting in data engineering or seeking to refine your skills for the DP-203 certification, this course provides a robust foundation and practical experience that can significantly benefit your career in data management and engineering. I highly recommend enrolling in this course to enhance your expertise and prepare for the future in data technologies.

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

Describe the various methods that can be used to ingest data between various data stores using Azure Data Factory

Perform common data transformation and cleansing activities within Azure Data Factory without using code Implement Slowly Changing Dimension using Azure Data Factory or Azure Synapse Pipelines

Use Azure Data Factory to orchestrate large scale data movement by using other Azure Data Platform and Machine Learning technologies

Integrate SQL Server Integration Services packages into an Azure Data Factory solution

Publish your Azure Data Factory work between different environments

Ingest data from Azure Data Share into Azure Data Factory pipelines to build automated ingestion pipelines

Practice Exam on Data integration at scale with Azure Data Factory or Azure Synapse Pipeline