Grow Data SKills | Most Affordable Courses | Become Top Data Professional

Light
Dark

Complete Data Engineering With Azure (5.0 BootCAMP) - Basic To Advance

By Shashank In Grow Data Skills

Live Classes ( From 2-August-2025 )
English
Completion Certificate

Demo Class Video

1 Year

Validity (From the date of Enrollment)

160 Hours

Duration

40

Sessions

15

Projects

Reserve Your Seat 🚨 Enrollment Opens On 7-July-2025 At 5 PM IST

This course includes

Content Duration160 Hours
Total Live Sessions40
Total Industry Projects15
AZURE & GCP Cloud
Quality Assignments & quizzes after each module
Interview preparation guide
Dedicated placement assistance
Resume & Linkedin profile making
Doubt solving in live classes and offline doubt support on private discord group
Certificate of completion

Tech stack you'll learn

Course Content

✅ Class - 1

What is Database?
Difference between Transactional Databases and NoSQL databases
What is DBMS & RDBMS?
Transactions & ACID Properties
Setup MySQL Workbench
DDL, DML, DQL, DCL
CREATE Command
INSERT Command
Integrity Constraints

✅ Class - 2

Alter Command
Drop, Truncate and Delete
Primary Key vs Foreign Key
Referential Integrity
Select Query, In-Built Functions, Aliases
UPDATE Command
Auto Increment in create table
Limit
Order By Clause
Conditional Operators
Logical Operators
Like Operation
User Defined Functions (UDFs)

✅ Class - 3

IS NULL, IS NOT NULL
Group By, Having Clause
Group Concat, Group RollUP
Sub Queries, IN and NOT IN
CASE-When
SQL Joins

✅ Class - 4

Exists and Not Exists
Window Functions
Frame Clause
Coalesce Function
Common Table Expressions - Iterative and Recursive

✅ Class - 1 (Theory Part Recorded)

BigData Fundamentals
5 V’s of BigData
Distributed Computation
Distributed Storage
Cluster, Commodity Hardware
File Formats
Types of Data
History of Hadoop
Hadoop Architecture & Components

✅ Class - 2 (Theory Part Recorded)

Map-Reduce Architecture
YARN Architecture

✅ Class - 3 (Theory Part Recorded)

Hive Complete Architecture
Hadoop Cluster Setup on GCP (Dataproc)

✅ Class - 4

Data Types in Hive
Create Database
Create Table
Load Data From Local
Load Data From HDFS
Internal Table
External Table
Array & Map Data Types
SerDe in Hive
File Formats in Hive - ORC, Parquet, Avro

✅ Class - 5

CSV SerDe
JSON SerDe
Parquet SerDe
ORC SerDe
Static Partitioning
Dynamic Partitioning
Bucketing
Map-Side Join, Bucket Map Join, Sorted Merge Join, Skew Join

✅ Class - 1 (Theory Part Recorded)

Kafka Cluster Architecture
Brokers
Topics
Partitions
Producer-Consumer, Consumer Group
Offset Management
Replicas
Commits
Sync & Async Commits

✅ Class - 2

Confluent Kafka Setup
Topic Creation
Schema Registry
Key, Value Message
Message in Kafka Topics based on Random and Constant Keys
Kafka Producer Code with Serialisation
Kafka Consumer Code with De-Serialization
Consumer Groups
Working with JSON, CSV Data
GCP Pub-Sub Setup
Producer & Consumer for GCP Pub-Sub Setup

✅ Class - 1 (Theory Part Recorded)

CAP Theorem
What is MongoDB and MongoDB Atlas?
MongoDB vs Relational Database
MongoDB features
MongoDB use cases and applications
MongoDB architecture
Node
Data Centre
Cluster
Data replication
Write operation
Read operation
Indexing

✅ Class - 2

MongoDB Atlas Setup
MongoDB Cluster Creation
MongoDB Compass Setup
Database & Collection in MongoDB
Connect with MongoDB Cluster from MongoDB Compass
Import JSON data in MongoDB Collection
Queries on MongoDB Collection from Python Application
KSQLdb in Confluent Kafka
Streams in KSQLdb
Tables in KSQLdb
Persistent Queries in KSQLdb
JOIN queries on streams in KSQLdb
McDonald's Payments Stream data ingestion from Kafka to MongoDB
Setup Orders & Payments Streams using KSQLdb
Setup windowed JOIN streams using KSQLdb
Setup MongoDB Sink Connector

✅ Class - 3 (Recorded)

CAP Theorem
What is Apache Cassandra?
Cassandra Database vs Relational Database
Apache Cassandra features
Cassandra use cases and applications
Cassandra architecture
Node
Data Centre
Cluster
Commit log
Mem-table
SSTable
Data replication
Read operation

✅ Class - 4 (Recorded)

Data Partitioning and Token
VNodes in Cassandra
Read Operation in Cassandra
Compaction in Cassandra
Gossip Protocol in Cassandra
Write consistency in Cassandra
Read consistency in Cassandra
Partition Key, Cluster Key, Row Key Declaration
Cassandra Setup Using Docker
CQL in Cassandra
Cassandra Free Tier Setup On DataStax
Queries in Cassandra using Python

✅ Class - 1 (Theory Part Recorded)

Problems with Hadoop Map-Reduce
What is Apache Spark?
Features of Spark
Spark ecosystem
RDD in Spark
Properties of RDD
How Spark perform data partitioning?
Transformation in Spark
Narrow Transformation vs Wide Transformation
Action in Spark
Read & Write operation in Spark are transformation or action?
Lazy evaluation in Spark
Lineage graph or DAG in Spark
How DAG looks on Spark Web UI?
Job, Stage and Task in Spark
What if Spark cluster capacity is less than the size of data to be processed?
Spark in-depth architecture and it's components
Spark with Standalone Cluster Manager Type
Spark with YARN Cluster Manager Type
Deployment modes of Spark Application
How DAG looks on Spark Web UI?
Internals of Spark Job over the cluster

✅ Class - 2 (Theory Part Recorded)

Persist and Caching in Spark
Storage Levels in Persist
How does data skewness occur in Spark?
Techniques to deal with data skewness
Repartition vs Coalesce
Example of Key Salting technique
RDD vs Dataframe vs Dataset
How to use Spark-Submit utility?
Memory management in Spark
Memory components in Executor Container
Dynamic occupancy mechanism
How to process 1 TB of data in Spark?
Resource allocation case study - 1 : 6 Nodes and each node have 16 cores & 64 GB RAM
Resource allocation case study - 2 : 6 Nodes and each node have 32 cores & 64 GB RAM
Resource allocation case study - 3 : When more memory isn't required for the executors
Broadcast and Accumulators in Spark
Different type of failures in Spark and how to resolve them
Out Of Memory failures
Code and Resource level optimizations in Spark
Best practices to design Spark Applications

✅ Class - 3

Spark Cluster Setup On GCP Dataproc
Spark Session creation
Create dataframe with custom schema
Read csv data from HDFS
Partitions and Partition size in Spark job
Select operation
withColumn operation
withColumnRenamed operation
Filter operation
Drop column operation
Drop Duplicates operation
Order By operation
Group By operation
Accumlator
Case-When operation
Window functions
Join & Broadcast join operation
Spark SQL, Register dataframe as table
Write CSV data in HDFS without partition key
Write Parquet data in HDFS
Write CSV data in HDFS with partition key
Write CSV data in HDFS with Coalesce
Read JSON Data in Spark and explode columns

✅ Class - 4

Execution of Spark application using Spark-Submit Utility
Monitor, Debug & Understand Spark Dag on Spark Web UI - Practical Example
What is Stream Processing?
Spark structured streaming
Spark streaming with word count example
Output modes in writeStream in Spark structured streaming
What if memory due to state management is full?
DStream vs Spark Structured Streaming
Spark structured streaming with File as source
Triggers in Spark structured streaming

✅ Class - 5

Checkpointing
Exactly once in spark structured streaming
Stateless and Stateful Processing
Global aggregation and Windowed aggregation
Windowing
Sliding window
Tumbling window vs Sliding window
When and why we should use windowing?
Windowed aggregations example
Arbitrary stateful transformations
Watermarking
Working example of handling delayed events using watermarking
Code implementation for Stateless spark structured streaming with source as Confluent Kafka Topic
Code implementation for Stateful spark structured streaming with source as Confluent Kafka Topic - Global aggregation and Windowed aggregation
Spark structure streaming pipeline implementation where Source is Confluent Kafka Topic and Destination is MongoDB

✅ Class - 1 (Theory Part Recorded)

What is orchestration in BigData?
Need of dependency management in Data Pipeline design
What is Airflow?
Architecture & Different Components of Airflow
Operators in Airflow
How to write Airflow DAG Scripts?
Attribute description
How to execute parallel tasks?

✅ Class - 2

Setup Airflow on GCP using Composer
Create and schedule Airflow Dag with sequential tasks using BashOperator and PythonOperator
Create and schedule Airflow dag with parallel tasks using BashOperator and PythonOperator
Airflow Exercise - 1 : End-To-End Airflow Dag to Create Dataproc Cluster, Run PySpark Job on cluster and Delete GCP Dataproc cluster
Airflow Exercise - 2 : Airflow Dag to support data backfilling via parameterized date inputs and use if Variables in Airflow
Project 1 - Flight Booking Data Pipeline with Airflow & CICD (Industrial Project)

Tech Stack - GitHub, GitHub Actions, Google Storage, PySpark, Dataproc Serverless, Airflow, BigQuery

✅ Class - 1

What is Databricks?
Unity Catalog
Delta Lake & Delta Tables
Databricks Account Setup on GCP
Workspace Setup
Metastore Setup
Managed & External Catalog Setup
Volumes In Databricks
Databricks Cluster Setup
PySpark Notebook Setup
Read/Write from Databricks Volume in PySpark Notebook
Create Delta table and Write data in PySpark using DeltaTable Python API
Write partitioned data in Delta table
Read from Delta table in PySpark
Time travel in Delta table (Read from specific version or timestamp)

✅ Class - 2

Project 1 - Order Tracking Event Driven Data Ingestion (Industrial Project)

Tech Stack: Google Storage, PySpark, Databricks, Delta Lake, Databricks Workflows, GitHub

Project 2 - UPI Transactions Real Time CDC Feed Processing (Industrial Project)

Tech Stack - Databricks, Spark Structured Streaming, Delta Lake

Project 3 - Travel Bookings Data Ingestion Pipeline With SCD2 Merge(Industrial Project)

Tech Stack - Databricks, PySpark, Google Storage, Delta Lake, Databricks Workflows, PyDeequ
What is DLT in Databricks?
How to create materialized views & streaming tables with DLT pipeline?
How to setup DLT pipeline job?
Validation & Execution of DLT pipeline with lineage
Checkpointing in DLT pipeline
Project 4 - Healthcare Delta Live Table Pipeline with Medallion Architecture (Industrial Project)

Tech Stack - Databricks, PySpark, Delta Lake, Delta Live Table Job

✅ Class - 1 (Theory Part Recorded)

OLAP vs OLTP
What is a Data Warehouse?
Difference between Data Warehouse, Data Lake and Data Mart
Fact Tables
Dimension Tables
Slowly changing Dimensions
Types of SCDs
Star Schema Design
Snowflake Schema Design
Galaxy Schema Design

✅ Class - 2

Case Study - 1: Uber Data Warehouse Design Case Study
Case Study - 2: AirBnB Data Warehouse Design Case Study

✅ Class - 1

Snowflake free tier account setup
Snowflake UI walkthrough
Load data from UI and create snowflake table
Hands On - Event driven data ingestion in snowflake table using SnowPipe

Tech Stack Used : Google Storage Bucket, GCP Pub-Sub, Snowflake
How to create and schedule task in snowflake

✅ Class - 2

Project - 1: News Data Analysis with event driven incremental load in Snowflake table(Industrial Project)

Tech Stack: Airflow, Google Cloud Storage, Python, Snowflake
Project - 2: Movie Booking CDC data real time aggregation in Snowflake Dynamic Table(Industrial Project)

Tech Stack: Python, Snowflake Dynamic Table, Snowflake Stream, Snowflake Tasks, Streamlit
Project - 3: Car rental data batch ingestion with SCD2 merge in snowflake table(Industrial Project)

Tech Stack: Python, PySpark, GCP Dataproc, Airflow, Snowflake

✅ Class - 3 (Recorded)

BigQuery Overview
BigQuery Architecture
Capacitor — Columnar format
Colossus — Storage
Dremel — Execution Engine
Borg — Compute
Jupiter — Network
Project - 1: IRCTC Streaming data ingestion into BigQuery(Industrial Project)

Tech Stack: Python GCP Storage, GCP Pub-Sub, BigQuery, Dataflow
Project - 2: Walmart data ingestion into BigQuery(Industrial Project)

Tech Stack: Python GCP Storage, Airflow, BigQuery

Azure Services Covered

Azure Blob Storage, Azure Functions, Azure Role-Based Access Control (RBAC), Azure Virtual Machines (VMs), Azure Logic Apps, Azure Service Bus (Queue, Topics), Azure Key Vault

Azure Stream Data Analytics, Azure Event Hubs, Azure Cosmos DB, Azure Data Factory, Azure SQL Database, Azure Synapse, Azure Delta Lake, Azure DevOPS

✅ Class - 1

Setup Free Trial Azure Cloud Account
Setup VSCode with Azure Extensions
Azure Blob Storage (Storage Account, Container, Blob)
Azure CLI Setup to interact with Azure Services
Read data from Azure Blob using Python
Azure Function & Azure Function App
HTTP Trigger based Azure Function
Deployment of Azure Function in Azure Function app from VSCode

✅ Class - 2

Implementation and Deployment of Azure Function with Blob Trigger
Azure Service Bus basics - Topic & Queue
Azure Service Bus Setup
Topic creation in Azure Service Bus
Write messages in Topic from Azure Console
Subscriber setup for Topic and Read (Peek and Receive Mode) messages from Azure Console
Implementation of Azure Logic App where Azure Function will listen to Blob trigger and publish blob details into Topics, inside Logic App it will read message content from Topic and send customize email with attachment
Implementation and deployment of Azure function app with Service Bus Topic trigger along with publishing mock data in Service Bus Topic using Python code
Azure Service Bus Queue basics
Create Queue from Azure Console
Read & Write messages in Queue from Azure Console
Implementation and deployment of Azure function app with Service Bus Queue trigger along with publishing mock data in Service Bus Queue using Python code

✅ Class - 3

Azure Virtual Machine Setup
SSH based login from terminal in VM
Azure SQL Database fundamentals
Setup Azure SQL database from Azure Portal
SQL commands for Azure SQL database using Query Editor
Azure Key-Vault basics
How to create and store secrets in Azure Key-Vault
Access & Manipulate data in SQL database using Python script (Access secrets from Key-Vault)
Azure Event Hub Fundamentals
Difference between Azure Event Hub & Kafka
Setup Azure event hub namespace from Azure Portal
Create event hub in namespace
Publish data in event hub using Python script
Create consumer group in event hub
Consume data from event hub using Python script
Azure Stream Analytics job basics
Create Inputs, Outputs & Query in Stream Analytics Job
Setup Stream Analytics job to read data from event hub in real time, apply window based aggregations and ingest data in SQL database

✅ Class - 4

Azure CosmosDB Fundamentals
Setup CosmosDB Account from Azure Portal
Create dataset and containers in CosmosDB
Connect & Manipulate data in CosmosDB using Python
Azure Data Factory Fundamentals
Create first Azure Data Factory Namespace
Connect ADF with Github
Setup Linked Services for ADLS & Snowflake in ADF
Create CSV file and Snowflake table datasets
Create DataFlow in ADF
Perform source, filter, aggregate & sink transformations in ADF
Debug Dataflow
Create Pipeline in ADF with DataFlow activity
Manual trigger for ADF pipeline
Azure Synapse Analytics fundamentals and Architecture
Setup first Azure Synpase Analytics workspace
Different features of Synapse Studio
Work with in-built and dedicated SQL pools
SQL Database under workspace
Read external files using in-built SQL pool queries
Create external tables using in-built sql pool
Work with SQL worksheet and create Schema, Internal & External tables in dedicated sql pool
Setup Spark SQL Pool
Create PySpark notebook in Synapse and write data in delta tables in Lake Database
Create linked services for ADLS and CosmosDB in Synapse
Data ingestion pipeline in Synapse Analytics

Challenges with traditional data lake storages?
What is open table format?
Challenges solved by open table formats?
What is small file problem?
How open table formats solved small file problem?
Apache Iceberg Overview
Apache Iceberg Architecture Overview
How Iceberg catalog works?
Metadata layer - Metadata files, Manifest lists and Manifest files
Data Layer - Data Files
Backend representation of Iceberg tables after CRUD operations
After Create Table Command
After Insert Command
After MERGE INTO / UPSERT Command
Copy-On-Write Approach (CoW)
Delete files
Positional Delete Files
Equality Delete Files
Merge-on-Read Approach (MoR)
How to choose between COW and MOR?
Behind the scene process while running Select commands on Iceberg tables
Create Table Command in Iceberg
Insert Command in Iceberg
Delete & Update Commands in Iceberg
Alter Command in Iceberg
Merge Query in Iceberg
Time travel Query (Read) in Iceberg
Compaction in Iceberg
Data pipeline with Iceberg on AWS & Snowflake (Case Study)
Medallion Architecture with Iceberg (Case Study)
Apache Hudi Overview
Apache Hudi Architecture
Data Sources
Hudi Core - ACID Guarantees, Incremental Pipelines, Multimodal Indexes, Managed Tables
Lakehouse Platform
Metadata
Data Sinks
Apache Hudi Storage Layout - Base Path, Meta Path, Partition Paths, Data Files
Apache Hudi Query Types
Snapshot Queries
Time Travel Queries
Read Optimized Queries (Only MoR tables)
Incremental Queries (Latest State)
Incremental Queries(CDC)
Create Table Command in Hudi
Alter Command in Hudi
Insert, Update & Delete Command in Hudi
Merge Query in Hudi
Time Travel QUERIES in Hudi
Case Study of Data pipeline of Apna with Hudi
Develop and execute PySpark application in GCP Dataproc environment for Write
Configure Glue catalog for Iceberg tables in Spark session along with GCS warehouse path
Build dummy dataframe and use createOrReplace() dataframe v2 api to create Iceberg table with partitions & other table properties
Perform append() operation on Iceberg table
Perform overwritePartitions() operation on Iceberg table
Perform merge query on Iceberg table
Understanding of iceberg metadata file after each write operation
Develop and execute PySpark application in GCP Dataproc environment for Read
Read iceberg table data for latest snapshot
Query snapshot information of Iceberg table
Read iceberg table for specific snapshot_id
Read iceberg table for specific committed timestamp

Trino Architecture & Query Lifecycle
Coordinator vs. Worker: roles and how work is split
From SQL → logical plan → physical plan → distributed execution
Data shuffling and result aggregation
Cluster Setup & Configuration
Installing Trino nodes and starting coordinator & workers
Basic inter-node connectivity
Defining catalogs to register data sources
Catalogs & Connectors
Hive connector for your data lake
Iceberg/Delta Lake support for ACID tables
JDBC (e.g. MySQL/Postgres) and Kafka connectors
ANSI-SQL & Advanced Querying
Joins, window functions, CTEs
Nested types (arrays, maps, structs)
Materialized views and runtime filtering
Performance Tuning
Memory pool limits & spill behavior
Cost-based planning with table statistics
Predicate pushdown to minimize I/O

✅ Project - 1: Flight Booking Data Pipeline with Airflow & CICD (Covered In Module 6)

Tech Stack - GitHub, GitHub Actions, Google Storage, PySpark, Dataproc Serverless, Airflow, BigQuery
✅ Project - 2: Order Tracking Event Driven Data Ingestion (Covered In Module 7)

Tech Stack - Google Storage, PySpark, Databricks, Delta Lake, Databricks Workflows, GitHub
✅ Project - 3: UPI Transactions Real Time CDC Feed Processing (Covered In Module 7)

Tech Stack - Databricks, Spark Structured Streaming, Delta Lake
✅ Project - 4: Travel Bookings Data Ingestion Pipeline With SCD2 Merge (Covered In Module 7)

Tech Stack - Databricks, PySpark, Delta Lake, Delta Live Table Job
✅ Project - 5: Healthcare Delta Live Table Pipeline with Medallion Architecture (Covered In Module 7)

Tech Stack - Databricks, PySpark, Delta Lake, Delta Live Table Job
✅ Project - 6: News Data Analysis with Event-Driven Incremental Load in Snowflake Table (Covered In Module 9)

Tech Stack: Airflow, Google Cloud Storage, Python, Snowflake
✅ Project - 7: Movie Booking CDC data real time aggregation in Snowflake Dynamic Table (Covered In Module 9)

Tech Stack: Python, Snowflake Dynamic Table, Snowflake Stream, Snowflake Tasks, Streamlit
✅ Project - 8: Car Rental Data Batch Ingestion with SCD2 Merge in Snowflake Table (Covered In Module 9)

Tech Stack: Python, PySpark, GCP Dataproc, Airflow, Snowflake
✅ Project - 9: IRCTC Streaming Data Ingestion into BigQuery (Covered In Module 9)

Tech Stack: Python, GCP Storage, GCP Pub-Sub, BigQuery, Dataflow
✅ Project - 10: Walmart Data Ingestion into BigQuery (Covered In Module 9)

Tech Stack: Python, Airflow, GCP Storage, BigQuery
✅ Project - 11: AirBnB CDC Ingestion Pipeline

Tech Stack: AZURE, Python, ADLS, CosmosDB, Azure Data Factory, Azure Synapse, SQL
✅ Project - 12: Fintech SQL Data migration into Azure Portal

Tech Stack: AZURE, Python, Azure SQL Database, Azure Synapse, ADLS, PySpark, SQL, Delta Tables
✅ Project - 13: BookMyShow Online Ticket Booking Stream data processing

Tech Stack: AZURE, Python, EventHub, Azure Stream Analytics Job, SQL, Synapse DWH
✅ Project - 14: Airlines Data Incremental data processing with CICD Process

Tech Stack: AZURE, ADLS, Logic Apps, Azure Data Factory, Azure Synapse, GitHub, Azure DevOPS
✅ Project - 15: Credit Card Transactional Analysis For Fraud Risk

Tech Stack: Python, PySpark, Google Storage, GCP Dataproc Serverless, GCP BigQuery, GCP Composer (Airflow), PyTest, GitHub, GitHub Actions (For CI/CD)
✅ Few exclusive projects around Iceberg, Hudi & Trino

Attention Seeking Resume Preparation and Interview Strategies
Strategies To Crack Tech Interviews
Linkedin Profile Making
How To Expand Your Professional Network On Linkedin
How To Use Various Job Portals
How To Approach For Referrals

Course Schedule

Course Start Date:

2-August-2025

Mode of the Course:

Live

Course Duration:

160 Hours

Total Sessions:

Total Projects:

Validity:

1 Year (Starting From The Date Of Enrollment)

Class Timing:

Saturday & Sunday [9:00 AM - 12:30 PM Live Teaching, 12:30 PM to 1:30 PM Live Doubt Session] (IST)

Class Duration:

3 Hours 30 Mins Live Teaching, 60 minutes Doubt Solving

Class Recording Provided:

Yes

Programming Language Used:

Python

Prerequisite:

Python

⚠️ Important Notice :

The video may not work on Linux due to DRM restrictions. It is only accessible on Chrome when using Windows or macOS.

Workaround: To access the video on Linux, you can create a Windows virtual machine (VM) and watch the video through the VM. Alternatively, you can use our Android or iOS application to view the video on your mobile device.

Instructor

Shashank Mishra

Shashank Mishra is a highly experienced Data Engineer with over 8+ years of experience at Expedia, Amazon, PayTM, and McKinsey & Company. An MCA graduate from NIT Allahabad, he specializes in architecting scalable data pipelines, cloud solutions, and advanced analytics platforms. Through his YouTube channel E-Learning Bridge—home to 182K+ subscribers—and a LinkedIn network of 182K+ followers, Shashank delivers hands-on tutorials and industry insights. He’s personally mentored over 15,000 aspiring data professionals to land roles at top tech firms. Passionate about project-driven learning, he combines practical expertise with clear guidance to help you master data engineering. Join him to transform raw data into actionable insights and launch your dream data career.