Grow Data Skills

Complete Data Engineering With AWS Basic To Advance (Self Paced)

LanguageEnglish
Validity 1 Year
Mode Recorded

Demo Class Video

INR 4800

Buy Now

This course includes

100+ hours recorded content
60 minute Recorded doubt session after each class
5 Industry level real world projects
Learn while solving real life examples in live lectures
BigData Projects on AWS Cloud
Projects will be covered from scratch
Hands on exercises & quizzes after each module
Career & Interview Preparation guidance recorded session
Resume Preparation recorded session
Linkedin Profile Making
Certificate of completion

Tools you'll learn

Course Content

MySQL Installation guide Connection & set up
DDL, DML, DCL in SQL
Data type of SQL
Create, Insert, Update, Alter, Delete, Drop, Truncate Operations
Views in SQL
Operators in SQL
WHERE clause, ORDER BY clause, GROUP BY & Having Clause
Aggregations Group Concat & Roll UP
CASE-WHEN Statement
Joins in SQL - Inner, Left, Right, Full, Self
Correlated subqueries IN, NOT IN, ANY, ALL, EXISTS, NOT EXISTS
Window Functions
Frame Clause in Window Functions
Common Table Expressions - Recursive, Iterative

5 V’s of BigData
Distributed Computation
Distributed Storage
Cluster, Commodity Hardware
File Formats
Types of Data
Hadoop Complete Architecture - HDFS, Map Reduce, YARN

Hive Architecture
Hadoop & Hive Setup on GCP Dataproc Cluster
HQL (Hive Query Language)
Working with different file formats in Hive
Partitioning and Bucketing in Hive
Optimized Joins in Hive
Optimizing Hive Queries

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

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
MongoDB Atlas Setup
Understanding different ways to communicate with MongoDB
Query data from MongoDB tables
Create APIs for MongoDB table data
Queries on MongoDB using Python
Bonus - Apache Cassandra Complete (Recorded Session)

Spark Complete Architecture
Memory Management in Spark
Spark Core, Dataframes & Functions in PySpark
Use SQL in PySpark
PySpark Structured Streaming With Kafka
Common Failures in Spark and their solutions
Optimization Techniques in Spark
Implement PySpark Application on GCP Dataproc Cluster
What is Databricks?
Databricks Setup
Create Cluster on Databricks
Data Import & Export in Databricks
PySpark Notebook on Databricks
Delta Table Operations
Excute PySpark Code on Databricks Cluster
Workflows On Databricks

Introduction of Airflow
Different Components of Airflow
Installing Airflow
Setup Airflow Using GCP Cloud Composer
Understanding Airflow Web UI
DAG Operators & Tasks in Airflow Job
Create & Schedule Airflow Jobs For Data Processing

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
Data Warehousing Case Studies
Inroduction of SnowFlake Data Warehousing Service
SnowFlake Architecture
Complete Setup of SnowFlake
Create Data Warehouse on SnowFlake
Analytical Queries on SnowFlake Data Warehouse
Undestanding SnowPark (Execute PySpark Application on SnowFlake)
What is GCP BigQuery?
GCP BigQuery Architecture
Complete Setup of GCP BigQuery
BigQuery Tables & Data Load
Create Data Warehouse on GCP BigQuery
Analytical Queries on GCP BigQuery Tables
Analytical Queries on GCP BigQuery Tables
Data Read & Write From BigQuery Tables in PySpark

S3
Lambda
IAM
CLOUDWATCH
EC2
SNS
SQS
Event Bridge Scheduler
Event Bridge Pipe
Kinesis
Kinesis Firehose
DynamoDB
Step Function
EMR
GLUE
RDS
ATHENA
REDSHIFT

Project 1: Quality Movie Data Analysis

Tech Stack:
- 📍 S3
- 📍 Glue Crawler
- 📍 Glue Catalog
- 📍 Glue Catalog Data Quality
- 📍 Glue Low Code ETL (With PySpark)
- 📍 Redshift
- 📍 Event Bridge
- 📍 SNS

Project 2: Gadget Sales Data Projection

Tech Stack:
- 📍 Python
- 📍 DynamoDB
- 📍 DynamoDB Streams
- 📍 Kinesis Streams
- 📍 Event Bridge Pipe
- 📍 Kinesis Firehose
- 📍 S3
- 📍 Lambda
- 📍 Athena

Project 3: Airline Data Ingestion

Tech Stack:
- 📍 S3
- 📍 S3 Cloudtrail Notification
- 📍 Event Bridge Pattern Rule
- 📍 Glue Crawler
- 📍 Glue Visual ETL (With PySpark)
- 📍 SNS
- 📍 Redshift
- 📍 Step Function

Project 4: Logistics Data Warehouse Management

Tech Stack:
- 📍 GCP Storage
- 📍 Airflow (GCP Composer)
- 📍 Hive Operators
- 📍 PySpark With GCP Dataproc
- 📍 Hive

Project 5: Sales Order & Payment Data Real Time Ingestion

Tech Stack:
- 📍 GCP Pub-Sub
- 📍 Python
- 📍 Docker
- 📍 Cassandra

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

Mode of the Course:

Recorded

Class Recording Provided:

Yes

Course Validity:

1 year

Programming Language Used:

Python

Prerequisite:

Check Our Python Bootcamp

Instructor

Shashank Mishra

Shashank Mishra is a seasoned Data Engineer with over 6 years of industry experience, worked at leading companies like Amazon, PayTM, McKinsey & Company and Expedia Group.

Why Data Engineer?

Map your interest to check if Data Engineer profile is a close match for you.

Who should become a Data Engineer?

Check if you are a good fit for a Data Engineer role.

Mandatory skill sets

You need to acquire these skill sets to become a Data Engineer.

Career growth of a Data Engineer

Growth of a Data Engineer from 0 to 10+ Years Of Experience.

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View Details

Complete Data Engineering With AWS - Basic To Advance (Self Paced)

INR 4800

Buy Now

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Complete Data Engineering With AWS Basic To Advance (Self Paced)

LanguageEnglish

Validity 1 Year

Mode Recorded

Tools you'll learn

Course Content

Module 1 - SQL

Module 2 - BigData Fundamentals & Hadoop

Module 3 - Apache Hive & Hadoop Cluster On GCP

Module 4 - Confluent Kafka & GCP Pub-Sub

Module 5 - MongoDB (NoSQL DataBase)

Module 6 - Apache Spark (PySpark) On Databricks & GCP Cloud

Module 7 - Apache Airflow With GCP Cloud Composer

Module 8 - Data Warehousing With SnowFlake & GCP BigQuery

Module 9 - AWS

Module 10 - Industrial Projects

Module 11 - Resume, LinkedIn & Interview Strategies

Course Schedule

Instructor

Shashank Mishra

Why Data Engineer?

Who should become a Data Engineer?

Mandatory skill sets

Career growth of a Data Engineer

Related Courses

Complete Data Engineering With AWS - Basic To Advance (Self Paced)

Namaste 🙏