Udemy – Data Engineering on AWS Vol 1 – OLAP & Data Warehouse

Detailed training (Level 350) on AWS Data Engineering Services Redshift, S3, Athena, Hive, Glue Catalog, Lakeformation

This is Volume 1 of Data Engineering course on AWS. This course will give you detailed explanations on AWS Data Engineering Services like S3 (Simple Storage Service), Redshift, Athena, Hive, Glue Data Catalog, Lake Formation. This course delves into the data warehouse or consumption and storage layer of Data Engineering pipeline. In Volume 2, I will showcase Data Processing (Batch and Streaming) Services.

You will get opportunities to do hands-on using large datasets (100 GB – 300 GB or more of data). Moreover, this course will provide you hands-on exercises that match with real-time scenarios like Redshift query performance tuning, streaming ingestion, Window functions, ACID transactions, COPY command, Distributed & Sort key, WLM, Row level and column level security, Athena partitioning, Athena WLM etc.

Some other highlights:

Contains training of data modelling – Normalization & ER Diagram for OLTP systems. Dimensional modelling for OLAP/DWH systems.

Data modelling hands-on.

Other technologies covered – EC2, EBS, VPC and IAM.

This is Part 1 (Volume 1) of the full data engineering course. In Part 2 (Volume 2), I will be covering the following Topics.

Spark (Batch and Stream processing using AWS EMR, AWS Glue ETL, GCP Dataproc)

Kafka (on AWS & GCP)

Flink

Apache Airflow

Apache Pinot

AWS Kinesis and more.

RAPIDGATOR:
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TURBOBIT:
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