Description
Data Engineering on AWS Vol 1 – OLAP & Data Warehouse. This course is the first in a complete data engineering series on AWS that focuses specifically on the data warehousing and analytics (OLAP) layer in the data pipeline. Course content covers key AWS services in detail, including S3, Redshift, Athena, Glue Data Catalog, and Lake Formation. Participants will work with real-world data engineering scenarios through extensive hands-on exercises with datasets ranging from 100 to 300 GB and beyond. Key practical topics include tuning query performance in Redshift, ingesting streaming data, Window functions, ACID transactions, the COPY statement, managing distribution and sort keys, workload management (WLM), and implementing row and column-level security. The course also teaches the fundamentals of data modeling and explores the differences between normalized modeling for OLTP and dimensional modeling for OLAP data warehouses. Additionally, essential AWS infrastructure topics such as EC2, EBS, VPC, and IAM are covered. This first volume builds the foundations of storage and analytics, setting the stage for the second volume, which will explore batch and stream processing with technologies such as Spark, Kafka, Flink, and Airflow.
What you will learn
- Understanding Data Engineering (Volume 1) on AWS using S3, Redshift, Athena, and Hive.
- Knowledge of Redshift, S3, and Athena up to level 350+ with practical work.
- Production Level projects and practical work to help candidates gain work-like training.
- Access and practice using datasets ranging from 100GB to 200GB in size.
- Learn Python for data engineering with practical work (functions, arguments, object-oriented programming (OOP) including class, object, self, modules, packages, multithreading, file management, etc.).
- Learn SQL for data engineering with practical work (database objects, CASE, Window functions, CTE (Common Table Expressions), CTAS (Create Table As Select), MERGE, Materialized View, etc.).
This course is suitable for people who:
- Data Engineers, Data Scientists, Data Analysts.
- Python developers, Application developers, Big Data developers.
- Database Administrators (DBAs), Big Data Administrators.
- Solutions Architects, Cloud Architects, Big Data Architects.
- Technical managers, engineering managers, project managers.
Course details
- Publisher : Udemy
- Teacher : Soumyadeep Dey
- Language: English
- Level : All Levels
- Lectures : 216
- Duration : 46 hours and 26 minutes
Course topics
Prerequisites for the Data Engineering on AWS Vol 1 – OLAP & Data Warehouse course
- Good to have AWS and SQL knowledge
Course images
Sample course video
Installation Guide
After Extract, view with your favorite player.
Subtitles: English
Quality: 720p
Download link
Downloadly
Rapidgator link
File(s) password: www.downloadly.ir
File size
14.54 GB
