Azure Data Engineer Training

Get Azure Data Engineer certification course with Golive Classes. We offer best Azure Data Engineer online training with real-time project material, useful notes, and details.

Instructor Golive Classes
Updated April 28, 2024

About Course

Looking for Azure Data Engineer training? Golive Classes provides Azure online training. Master Azure Data Engineer with Golive Classes. We provide the best Azure Data Engineer online training in Hyderabad and all over India.

Join Azure BI training with Golive Classes. We at Golive Classes provide the world-class Azure BI certification course. The Azure BI training is designed to ensure that you learn & master the concepts of it and pass the certification exam on the first attempt. You get to learn the Azure BI along with SQL. Our training will help you design and implement data storage and develop data processing in Azure. Get your hands dirty with Azure BI along with SQL. The practical hands-on learning approach followed in the course will ensure you get job-ready by the end of it.

We, at Golive Classes, provide you with specialized Azure BI training, from beginner to advanced level. We have experienced Data engineer experts who will guide and help you understand Azure BI (Business Intelligence) concepts. In addition, our team offers a customized Azure BI Course Online curriculum to meet the standards of the current industry.

Azure Data Engineer

Azure Data Engineer

What is Azure BI Certification?

A Certified Azure BI works on integrating, transforming, and consolidating data from various structured and unstructured data systems into structures that are suitable for building analytics solutions for any size of the company.

Become a Certified Data Engineer in Azure with our Azure BI online training program and

  • Design and implement data storage.
  • Design and develop data processing.
  • Design and implement data security.
  • Monitor and optimize data storage and data processing.
Here’s why one should opt Azure BI career:
  • Certified Azure BI is one of the fastest-growing and on-demand roles among Data Science technologies.
  • There isn’t a better time to start learning these Microsoft Azure Data Solution technologies if you are among the aspired ones.
  • An average Azure BI earns $106,157 per year.
Who is this Azure BI online training for?
  • For absolute Beginners in Azure.
  • Database Developers and Administrators
  • Business Intelligence (BI) Developers
  • Data Engineers, Data Scientist, Data Analyst, and similar profiles
  • Other on-premises Database profiles were curious about learning how to implement these technologies in Azure.
  • Anyone aspiring his/her career as an Azure BI.
What are the prerequisites for this Azure BI training?
  • Basic concepts of Databases.
  • Basic knowledge of T-SQL
  • Microsoft Azure trial subscription. (Do not have an azure account? we are here to assist you in creating a free subscription).
Why choose Golive Classes for Azure BI training?

With Golive classes Azure BI training, we provide:

  • Real-time concepts with case studies
  • Project Explanation
  • Interview Questions
  • Resume preparation
  • Technical Assistance even after Course Completion
  • Career Guidance
  • Lifetime access to video recordings.
  • The assistance provides in consulting and placement
  • Free other courses will be provided free of cost.

Course Curriculum

SQL Server.
  1. Introduction to Relation Databases
  • Introduction to database concepts like Data, Database, Entity, attribute, and ER Diagrams.
  • How to connect SQL Server using SSMS (SQL Server Management Studio)
  • Installation of SQL Server and SSMS
  1. DDL (Data Definition Language)
  1. DQL (Data Query Language)
  1. DML (Data Manipulation Language)
  • INSERT – is used to insert data into a table.
  • UPDATE – is used to update existing data within a table.
  • DELETE – is used to delete records from a database table.
  1. Constraints
  1. Data Types
  • Different Types of data types available in SQL Server
  1. Various Clauses
  • Where, Group By, Order By, TOP N, DISTINCT, ROW_NUMBER, RANK (), CASE
  1. Functions
  • Aggregate Functions (SUM, MIN, Max, AVG, COUNT), String Functions
  1. Operators
  1. Joins
  • Inner Joins, Left Join (Left Outer Join), Right Join (Right Outer Join)
  1. Set Operations
  • Union, Union ALL, Intersect
  1. Views, Functions, and Stored Procedures
  2. Usage of Temp table, Table variable, CTE.


Azure BI (Azure Blob Storage, Azure Data lake, AZURE SQL DB, AZURE data factory & Azure Synapse analytics).
  1. Introduction to Azure.
  • Introduction to Azure portal, Subscriptions, and services available in azure.
  • How to create free subscriptions and various services in azure.
  1. Introduction to Azure Blob Storage.
  • Introduction
  • How to create blob storage.
  • Blob storage resources
    • The storage accounts
    • A container in the storage account
    • A blob in a container
  • Transfer data to and from Azure Storage
  1. Introduction to Azure Data Lake.
  • Introduction
  • How to create Azure Data Lake.
  • Data lake features
  • Transfer data to and from Azure Storage
  1. Azure SQL Database.
  • What is Azure SQL DB
  • Different deployments of SQL in Azure.
  • Azure SQL Managed Instance
  • How to create Azure SQL Server
  • Create database, schema, table, view, and stored procedures.
  • Elastic Pool, Different kinds of pricing tiers
  • How to query data from Azure SQL server using on-premises SSMS and cloud.
  • Data exchange between azure SQL database to azure storage like a blob and Data Lake & Vice -versa.
  • What is poly base in Azure SQL?
  • What is an external table?
  • Data factory use case for data exchange from azure SQL database to various destinations.
  1. Azure Data Factory.
  • Overview of ETL/ELT processes.
  • Cloud & On-premises ETL tool comparison.
  • Azure data factory components like Pipeline, Dataset, Linked service, Activities, and data flows.
  • Integration run time- Different Types of integration run times (Auto, Self-hosted & SSIS).
  • Develop pipelines using various activities like copy activity, stored procedure activity, Lookup Activity, Get Metadata activity, Delete activity, Wait for activity, Execute package activity, etc.
  • Iteration & Conditions – IF, For Each, until…
  • Working with different sources and sinks.
  • Data flow overview and transformation in the data flow.
  • Integration Runtime, different Types of Integration Run times
  • Logic apps- how to call logic app (RESTAPI) from ADF Web activity.
  • Pipeline debug and monitoring
  • Parameters & Variables usage in pipelines.
  • Error handling
  • Schedule and trigger the pipelines
  • What are ARM Templates using for deployment?
  • How to deploy data factory code from dev to q to prod environment.
  1. Azure Synapse analytics.
  • Introduction to Synapse analytics.
  • Synapse analytics architecture.
  • Synapse SQL: Complete T-SQL based analytics
    1. Dedicated SQL pool (pay per DWU provisioned)
    2. Serverless SQL pool (pay per TB processed)
    3. Spark: Deeply integrated Apache Spark.
    4. Synapse Pipelines: Hybrid data integration
    5. Studio: Unified user experience
  • Features of Azure Synapse Analytics
  • Table distribution – Replicate, Round-Robin & HASH
  • External tables, Polybase
  • Load data into synapse SQL using various options like poly base, Bulk copy
  • Power BI data refresh from Azure synapse data warehouse.
  • ADF pipeline use case for data extraction.
  1. Azure Data bricks.
  • Introduction to Azure Data bricks
  • How to create Data bricks-free account.
  • Workspace, Notebooks
  • Basics of Spark
  • How to mount Data lake to Data bricks using Scala
  • Reading data from Blob Storage and writing into Azure SQL/synapse
  • Reading data from Data Lake Storage and writing into Azure SQL/synapse
  • Explore, analyze, Clean, Transform and load data in data bricks using Python and SQL
  • Use cases.
  1. Real-Time Project explanation and Practice.
  • Introduction to different data warehouses, on-premises and cloud data warehouses, dimension modeling (star & Schema), Dimension, and fact tables.
  • How to gather project requirements, Scrum task details.
  • Tools used in projects like SQL Server on-premises, ETL(ADF), and destination (Synapse)
  • How to handle delta and full loads in the ETL process.
  • Using Power BI how to prepare using Synapse data warehouse.

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Course Content

Overview of Data Engineering

  • Definition and scope of data engineering.
  • The evolving role of the data engineer.

Real-World Applications of Data Engineering

Key Responsibilities of Data Engineers

Trends and Challenges in Data Engineering

Essential Skills for Data Engineers

Introduction to SQL

Foundational SQL Operations

Intermediate SQL Operations

Advanced SQL Concepts

SQL in Practice

Core Concepts of Cloud Computing

Exploring Azure Services

Azure Security, Privacy, Compliance, and Trust

Azure Pricing and Support

Azure Storage Deep Dive

Hands-on Blob Storage

Azure File and Queue Storage

ADF Components and Architecture

Building Data Integration Solutions

Orchestration and Monitoring

Dataflow Patterns and Debugging

Spark Core Concepts

Understanding Spark’s Execution Engine

Databricks Environment Setup

PySpark for Data Engineers

Delta Lake on Databricks

Deep Dive into Spark SQL

Delta Lake Tables in Practice

Logic Apps for Workflow Automation

Synapse Workspace

Synapse SQL Pools

Data Integration and Exploration

Advanced Analytics and Security

Project and Live Examples

Azure Data Engineer Training
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