Data Engineering Vol 1 (aws)

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Data Engineering Vol 1 (aws)
Published 1/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.63 GB | Duration: 13h 18m
Detailed training (Level 350) on AWS Data Engineering Services Redshift, S3, Athena, Hive, Glue Catalog, Lakeformation​

What you'll learn
Understand Data Engineering (Volume 1) on AWS using S3, Redshift, Athena and Hive
Know Redshift, S3 and Athena up to Level 350+ with HANDS-ON
Production level projects and hands-on to help candidates provide on-job-like training
Get access to datasets of size 100 GB - 200 GB and practice using the same
Learn Python for Data Engineering with HANDS-ON (Functions, Arguments, OOP (class, object, self), Modules, Packages, Multithreading, file handling etc.
Learn SQL for Data Engineering with HANDS-ON (Database objects, CASE, Window Functions, CTE, CTAS, MERGE, Materialized View etc.)
Requirements
Good to have AWS and SQL knowledge
Description
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)FlinkApache AirflowApache PinotAWS Kinesis and more.
Data Engineers, Data Scientists, Data Analysts,Python developers, Application Developers, Big Data Developers,Database Administrators, Big Data Administrators,Solutions Architect, Cloud Architect, Big Data Architect,Technical Managers, Engineering Managers, Project Managers
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