Data Engineering on AWS Vol 1 - OLAP & Data Warehouse | Udemy

[franktuchel]

[center][img]https://i.imgur.com/PYPQ81a.png[/img][/center]

[center][b]Data Engineering on AWS Vol 1 - OLAP & Data Warehouse | Udemy[/b]
English | Size: 16.27 GB
Genre: eLearning[/center]

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

[b]What you'll learn[/b]
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.)

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.

[b]Who this course is for:[/b][b][/b]
Data Engineers, Data Scientists, Data Analysts
Python developers, Application Developers, Big Data Developers
Database Administrators (DBA), Big Data Administrators
Solutions Architect, Cloud Architect, Big Data Architect
Technical Managers, Engineering Managers, Project Managers

[center][img]https://i.imgur.com/yMNlxlr.png[/img][/center]

[b]DOWNLOAD FROM RAPIDGATOR[/b]

This is the hidden content, please

• Sign In
• or
• Sign Up

[b]DOWNLOAD FROM TURBOBIT[/b]

This is the hidden content, please

• Sign In
• or
• Sign Up

[b]DOWNLOAD FROM NITROFLARE[/b]

This is the hidden content, please

• Sign In
• or
• Sign Up

[b]If any links die or problem unrar, send request to[/b]

This is the hidden content, please

• Sign In
• or
• Sign Up