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    Learn Aws Data Engineering

    Posted By: ELK1nG
    Learn Aws Data Engineering

    Learn Aws Data Engineering
    Last updated 12/2020
    MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 511.69 MB | Duration: 1h 22m

    ETL & BI on AWS Cloud

    What you'll learn

    Data engineering concepts and AWS services

    Fetching data from external Rest Api

    Fetching data from SFTP server

    Ingesting data into a Database

    Creating Serverless Data Lake using S3 and Athena

    Creating Glue ETL jobs and Workflows

    Transforming data into Parquet format

    Learn how to store data in S3 Data lakes using Parquet columnar file formats

    Requirements

    Hands on expertise on Python & Sql is a must

    An active AWS account

    Description

    A hands on course that covers majority of the typical data engineering / ETL scenarios. In this course you will learn:Different services and concepts of AWS data engineeringCreating serverless data lake using S3, Glue and AthenaIngesting data using Rest ApiIngesting data using Sftp serverIngesting data into Database (AWS RDS - Postgre SQL)Incremental data loadingPrerequisites:An active AWS accountPython / SQL knowledge

    Overview

    Section 1: Introduction

    Lecture 1 Introduction

    Section 2: Data Engineering Services

    Lecture 2 S3

    Lecture 3 Athena

    Lecture 4 Glue

    Lecture 5 Lambda

    Lecture 6 RDS

    Lecture 7 SQS

    Lecture 8 SNS

    Lecture 9 Kinesis

    Section 3: Live Demos

    Lecture 10 Serverless Datawarehousing

    Lecture 11 Ingest data from a Rest Api

    Lecture 12 Ingest data into a SQL database (Postgre SQL)

    Lecture 13 Incremental data Loading

    Lecture 14 Ingest data from a SFTP server

    Beginner python developers curious for data science,Data engineers,BI/ ETL Developers,Data Scientists / Analysts,Anyone from technical background who wants to learn Data engineering in AWS,Software developers who want to learn different ways to ingest data into AWS and build a datawarehouse