The description
Data Engineering Master Class using AWS Analytics Services is the name of the Data Engineering Master Class using AWS Analytics Services published by Udemy Academy.
Data engineering involves creating data pipelines to get data from multiple sources into data lakes or data warehouses and then from data lakes or data warehouses to downstream systems. In this course, I will show you how to create data engineering pipelines using AWS Data Analytics Stack. It includes services such as Glue, Elastic Map Reduce (EMR), Lambda Functions, Athena, EMR, Kinesis and many more.
Here are the high-level steps you will take in the course.
- Set up development environment
- Get started with AWS
- Storage – Everything on AWS s3 (Simple Storage Service)
- User-Level Security – Managing Users, Roles, and Policies Using IAM
- Infrastructure – AWS EC2 (Elastic Cloud Compute)
- Data ingestion using AWS Lambda functions
- Overview of AWS Glue Components
- Configure Spark History Server for AWS Glue Jobs
- Dive into the AWS Glue Catalog
- Exploring AWS Glue Job APIs
- AWS Glue Job Bookmarks
- Pyspark development cycle
- Get started with AWS EMR
- Deploying Spark Applications Using AWS EMR
- Streaming pipeline using AWS Kinesis
- Consuming data from AWS s3 using ingested boto3 using AWS Kinesis
- Populating GitHub data to AWS Dynamodb
- Introducing Amazon AWS Athena
- Amazon AWS Athena using the AWS CLI
- Amazon AWS Athena using Python boto3
- Getting Started with Amazon AWS Redshift
- Copy data from AWS s3 to AWS Redshift tables
- Develop applications using AWS Redshift Cluster
- AWS Redshift Arrays with Distkeys and Sortkeys
- AWS Redshift Federated Queries and Spectrum
Who should attend ?
- Entry-level or intermediate data engineers who want to learn AWS Analytics services for data engineering
- Intermediate application engineers who want to explore data engineering using AWS Analytics services
- Data and analytics engineers who want to learn data engineering using AWS Analytics Services
- Testers who want to learn Databricks to test data engineering applications built using AWS Analytics Services
What you will learn in Data Engineering Master Class Using AWS Analytics Services Course :
- Data engineering leveraging features of AWS Analytics
- AWS Essentials such as s3, IAM, EC2, etc.
- Understanding AWS s3 for cloud-based storage
- Understand the details related to virtual machines on AWS called EC2
- Managing AWS IAM Users, Groups, Roles, and Policies for Role Based Access Control (RBAC)
- Managing Tables Using the AWS Glue Catalog
- Engineering Batch Data Pipelines Using AWS Glue Jobs
- Orchestrating Batch Data Pipelines Using AWS Glue Workflows
- Executing Queries Using AWS Athena – Serverless Query Engine Service
- Using AWS Elastic Map Reduce (EMR) Clusters to Build Data Pipelines
- Using AWS Elastic Map Reduce (EMR) Clusters for Reporting and Dashboards
- Data ingestion using AWS Lambda functions
- And…..
Course details:
Editor: Udemy
Instructor: Durga Viswanatha Raju Gadiraju,Asasri Manthena,Perraju Vegiraju
French language
Level of training: Advanced
Number of courses: 434
Duration of training: 26 hours 15 minutes
Masterclass in Data Engineering Using AWS Analytics Services Course Content:
Requirements:
- Programming experience with Python
- Data engineering experience with Spark
- Ability to write and interpret SQL queries
- This course is ideal for experienced data engineers who want to add AWS Analytics services as key skills to their profile.
Pictures :
Simple video:
Installation guide :
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Subtitle: English
Quality: 720p
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File password(s): ngaur.com
File size:
9.12 GB