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Azure Data Engineering

COURSE HIGHLIGHTS

  • 10+ Yrs Of Experienced Real Time Trainers
  • Competitive Course Content As Per Current Market.
  • Real Time Project End To End Will Be Covered In Every Course.
  • Course Will Be Start From Basic Level To Advanced Level
  • All The Real Time Tools Learn In The Part Of Course
  • Daily Assignments And Monitoring Your Work
  • Weekly Written Tests Will Be Conducted
  • Real Time Scenarios And Interview Questions Discussion
  • Mock Interviews With Feedback And Suggestions If Any.
  • Sharing All The Documents Used In Real Time Projects.
  • After Course Completion Also We Will Address Your Queries On Weekly Q&A Session.
  • Recordings Access For Lifetime.

Our Workflow

Azure Data Engineering Course Content

 

  1. Introduction
  1. Azure Fundamentals
  2. IaaS
  3. PaaS
  4. SaaS
  5. Subscription and Accounts
  6. Resource Manager
  7. Azure Portal & Cloud Shell
  8. Managing Costs & Budgets
  1. Azure Regions and Availability Zones
  1. Networking concepts & Security
  1. Azure Virtual Machines
  1. Azure Data Lake Storage
  2. Definition
  3. Azure Data Lake-Key Components
  4. How it stores data?
  5. Azure Data Lake Storage Gen2
  6. Why Data Lake?
  7. Lab: Data Lake Architecture (real time use cases)
  1. Azure SQL
  2. Azure SQL DB as service
  3. Azure SQL Pools
  4. Azure SQL on VM
  5. Azure Managed Instance
  6. Lab: Real time use case
  1. Azure Data Factory (ETL/ELT)
  2. What is ADF?
  3. Pipelines
  4. Activities
  5. Datasets
  6. Linked Services
  7. Integration Services
  8. Triggers
  9. Lab: Real time use case
  1. Azure Synapse Analytics (SQL Datawarehouse)
  2. What is Azure Synapse Analytics?
  3. Synapse Architecture
  4. Serverless SQL Pools
  5. Dedicated SQL Pools
  6. Apache Spark Pool
  7. Lab
  1. Azure Databricks
  2. What is Azure Databricks?
  3. Workspace
  4. Spark Overview
  5. Databricks Architecture
  6. Databricks Data Science & Engineering
  7. Lab
  1. Datawarehouse core concepts
  2. Slowly Changing Dimensions (SCD & types)
  3. Data modelling (Star & Snowflake Schemas)
  4. Facts
  5. Dimensions
  1. Hands on with real time use case
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