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    Azure Data Factory Deployment Essentials: A Devops Approach

    Posted By: ELK1nG
    Azure Data Factory Deployment Essentials: A Devops Approach

    Azure Data Factory Deployment Essentials: A Devops Approach
    Published 12/2023
    MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
    Language: English | Size: 2.49 GB | Duration: 2h 44m

    Hands-On Deployment: Mastering Azure Data Factory, Azure Data Lake, and Azure SQL DB with DevOps Practices

    What you'll learn

    Continuous Integration (CI) for Data Pipelines

    Version Control for Data Projects

    Introduction to Azure DevOps

    Creating Your First Azure Data Factory Project

    Introduction to Azure Data Factory Components

    Provision Azure Data Lake Storage for effective data management

    Requirements

    Internet connections

    mobile / laptop / pc

    Headphone

    Description

    Unlock the full potential of Azure Data Factory by mastering the art of deployment with a hands-on, practical approach. In this comprehensive course, you'll delve into the intricacies of data orchestration, ETL, and deployment using Azure Data Factory. From setting up your infrastructure to implementing advanced deployment strategies, this course covers it all.Key Highlights:Infrastructure Setup: Learn to configure Azure Data Lake, Azure SQL Database, and establish the groundwork for your data projects.Azure Data Factory Basics: Understand the components of Azure Data Factory, create pipelines, and explore data movement and transformation techniques.DevOps Integration: Dive into the world of DevOps and discover how to leverage Azure DevOps for version control, continuous integration, and continuous deployment in data projects.CI/CD for Data Pipelines: Automate your build and deployment processes, ensuring seamless integration and efficient management of your data pipelines.Advanced Deployment Scenarios: Explore parameterization, dynamic configurations, monitoring, and logging strategies for robust and scalable data pipelines.Real-World Case Studies: Gain insights from real-world projects, including large-scale data migration and real-time data integration, and apply learnings to your own deployments.Troubleshooting and Best Practices: Learn to debug issues, implement best practices, and optimize your data pipelines for performance.Future Trends and Updates: Stay ahead of the curve by exploring emerging trends in data integration and understanding how to adapt to future updates in Azure.Who Should Enroll:Data engineers, analysts, and professionals seeking a comprehensive understanding of Azure Data Factory deployment using DevOps practices. Whether you're a beginner or an experienced user, this course caters to all levels, providing actionable insights and practical skills for successful data project deployment.

    Overview

    Section 1: Introduction

    Lecture 1 Introduction

    Lecture 2 Create Azure Account

    Section 2: Setting Up Your Dev Infrastructure

    Lecture 3 Define your naming convention-Recommended Naming Components

    Lecture 4 Create Azure SQL DB

    Lecture 5 Create Azure Data Factory And Azure Data Lake G2

    Lecture 6 Configure Our Source Data Base

    Section 3: Azure Data Factory Basics

    Lecture 7 Overview Of Azure Data Factory

    Lecture 8 Different Components Of Azure Data Factory And Its Workings

    Lecture 9 How To Create Linked Services

    Lecture 10 How To Create Data Sets

    Lecture 11 Create New Pipeline And Execute Your First ADF Project

    Section 4: Introductions To Azure DevOps

    Lecture 12 What is Azure DevOps

    Lecture 13 How To Create Azure DevOps Account

    Lecture 14 How To Create New Organizations In Azure DevOps

    Lecture 15 How To Create And Configure New Projects In Azure DevOps

    Section 5: Continues Integration - Azure Data Factory-Azure DevOps Integrations

    Lecture 16 Azure Data Factory Azure DevOps integrations

    Lecture 17 Create A New User

    Lecture 18 Grant Access To New User

    Lecture 19 Fix Error

    Lecture 20 Create Pull Request And Integrate All the changes to live

    Section 6: Azure Key Vault: Secure Our Connections

    Lecture 21 Create Azure Key Vault

    Lecture 22 Create Secrets In Azure Key Vault And Store Connections Details

    Lecture 23 Create Secrets In Azure Key Vault & Store Connections Details

    Lecture 24 Configure Azure Data Factory To Use Azure Key Vault

    Section 7: Setting Up Your UAT Infrastructure

    Lecture 25 Create UAT Resources

    Lecture 26 Configure UAT Azure Key Vault Secrets

    Lecture 27 Add New Versions In Azure Key Vault Secrets

    Lecture 28 Configure Azure SQL DB -Northwind Data bases

    Section 8: Setting Up Your Prod Infrastructure

    Lecture 29 Create Prod Resources

    Lecture 30 Configure PROD Azure Key Vault Secrets

    Section 9: Continues Deployment- Azure Data Factory-Azure DevOps Deployment

    Lecture 31 Grant Azure Data Factory (UAT & Prod) To Access Key Vault And Create ARM templat

    Lecture 32 Create Release Pipeline In Azure DevOps

    Lecture 33 Configure Azure DevOps Artifacts

    Lecture 34 Create And Configure Stage -UAT

    Data Engineers and Analysts: Individuals working with data integration, ETL processes, and data orchestration who want to enhance their skills using Azure Data Factory and implement DevOps practices in their workflows.,Azure Enthusiasts: Professionals interested in harnessing the power of Azure services specifically for data engineering, gaining practical experience with Azure Data Factory, and understanding how to seamlessly deploy data solutions in the cloud.,DevOps Practitioners: Those seeking to integrate DevOps principles into the data integration landscape, automate workflows, and optimize collaboration between data and IT teams.,IT Professionals and Architects: Professionals responsible for designing, implementing, or overseeing data projects in Azure who want to stay updated on best practices, emerging trends, and advanced deployment strategies.,Students and Aspiring Data Professionals: Individuals pursuing a career in data engineering or related fields who want to build a strong foundation in Azure Data Factory and DevOps to stand out in the job market.,Business Intelligence Professionals: BI developers and professionals interested in extending their knowledge to include end-to-end data engineering processes, from data ingestion to deployment.