Azure Data Engineer End to End Training

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Course Content

Azure Data Engineer End to End Training

  • Azure Data Engineering Introduction
    01:24:09
  • Traditional On-Premises Deployment vs. Cloud Services
    01:15:23
  • Azure Data Factory Simplifying Data Movement and Transformation
    01:08:19
  • Understanding Azure Data Factory
    01:02:38
  • Introduction to Azure Portal
    01:06:02
  • Creating Cloud Storage Accounts
    01:06:39
  • Implementing Metadata-Driven Data Movement from Blob to Data Lake
    58:42
  • Large-scale data copying pipeline.
    01:04:40
  • Creating linked services in Azure.
    01:00:32
  • Creating an Azure DataBrick Service Exploring Spark Architecture and Differences
    34:45
  • Pipeline activities and metadata explained.
    52:09
  • Data Validation and Copy using Azure Data Factory Service
    51:46
  • 13-P1 – Moving data from HTTP to ADLs
    58:39
  • 13-P2-Loading Multiple Files from Blob Storage to Delimited Text File Target
    49:50
  • Iterating and Moving Multiple Files with Azure Data Factory
    58:39
  • Moving Data from SQL to Data Lake and Vice Versa
    58:52
  • Essentials of SQL Database Creation and Connectivity
    01:11:09
  • Moving Multiple Tables from Azure SQL Database to Data Lake
    52:39
  • Maximizing Your Pipeline Efficiency with Tumbling Window-Based Triggers
    50:47
  • Introduction to Azure Key Vault and its role in securing credentials
    52:41
  • Securely Configuring Authentication for Azure Data Factory
    01:05:43
  • Understanding Authentication Types for Securing Azure Data Factory
    55:36
  • Managing Pipelines and Environments with Code Repositories
    56:42
  • Configuring Azure Data Factory with Azure DevOps and GitHub Repositories
    51:06
  • Introduction to Data Flows and Transformations in ADF
    57:37
  • Exploring Data Flows in Azure Data Factory
    01:04:43
  • Exploring Data Transformations in Pipeline A Practical Guide
    35:22
  • Using Conditional Split Transformation in Data Flow
    49:34
  • Data Set Comparison Using the Exist Transformation in Data Flows
    48:36
  • Derived Column Transformation in Data Flows
    47:29
  • Mastering Data Flows and Transformations
    48:40
  • How to Unpivot Data in Azure A Step-by-Step Guide
    56:41
  • Union vs. Union All Transformations
    50:58
  • Troubleshooting Common Errors in ADF Mapping Data Flows
    53:34
  • Authentication Methods for Azure Data Lake Gen2 Link Services
    50:29
  • Debugging and Testing Data Flows for Improved Efficiency
    50:45
  • Pre and Post-Copy Scripts Best Practices for Loading Data into a Data Lake
    39:42
  • Azure Databricks for Efficient Big Data Transformations
    59:52
  • Transforming Big Data with Azure Databricks
    49:23
  • Maximizing Performance and Efficiency with Azure Databricks
    52:51
  • Connecting to Blob Storage
    42:36
  • Mastering Pi Spark API for Effective Data Analysis
    48:24
  • Databricks and Azure Storage Integration
    42:36
  • Efficient Data Storage and Management with Databricks and ADF
    50:09
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