Description
Data Engineering Vol2 AWS: Data Processing – Spark & Kafka is a course on how to build scalable, cloud-native data processing pipelines using industry-standard tools on AWS, published by Udemy Online Academy. This is a hands-on, project-based course that teaches you how to build scalable, cloud-native data processing pipelines using industry-standard tools on AWS. The course focuses on Apache Spark for large-scale distributed computing and Apache Kafka for real-time data streaming, and shows you how to integrate both with AWS services such as EMR, MSK, S3, Lambda, and Glue. You will learn how to design pipelines that efficiently ingest, transform, and deliver data, manage batch and broadcast workloads, optimize performance, and implement end-to-end architectures used in real-world data engineering environments.
In this course, I will talk about open source data processing technologies – Spark and Kafka, which are the most widely used and popular data processing frameworks for batch and stream processing. In this course, you will learn Spark from level 100 to level 400 with practical exercises and real projects. I will also introduce you to Data Lake on AWS (i.e. S3) and Data Lakehouse using Apache Iceberg. This course provides you with practical exercises that correspond to real-time scenarios such as Spark batch processing, stream processing, performance tuning, stream consumption, window functions, ACID transactions on Iceberg, etc.
What you will learn in Data Engineering Vol2 AWS : Data Processing – Spark & Kafka:
- In-depth review of Spark and Kafka using AWS EMR, Databricks, MSK
- Understanding Data Engineering (Volume 2) on AWS using Spark and Kafka
- Batch and Stream Processing using Spark and Kafka
- Production-level and hands-on projects to help candidates deliver similar training on the job
- Access and practice 100-200 GB datasets
- Learn Python for data engineering in a hands-on way (functions, arguments, OOP (class, object, self), modules, packages, multithreading, file management, etc.)
- Learn SQL for data engineering in a hands-on way (database objects, CASE, window functions, CTE, CTAS, MERGE, materialized view, etc.)
- AWS Data Analytics Services – S3, EMR, Databricks, MSK
- And…
Course specifications
Publisher: Udemy
Instructors: Soumyadeep Dey
Language: English
Level: Introductory to Advanced
Number of Lessons: 255
Duration: 60 hours and 41 minutes
Course topics
Data Engineering Vol2 AWS : Data Processing – Spark & Kafka Prerequisites
Good to have AWS and SQL knowledge
Pictures
Data Engineering Vol2 AWS : Data Processing – Spark & Kafka introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: None
Quality: 720p
Downloadly link
Rapidgator link
File password (s): www.downloadly.ir
Size
22.4 GB
