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 route data from multiple sources to data lakes or data warehouses, and then from data lakes or data warehouses to downstream systems. In this course, I’ll walk you through how to build data engineering pipelines using the AWS Data Analytics stack. It includes services such as Glue, Elastic Map Reduction (EMR), Lambda Functions, Athena, EMR, Kinesis and many others.
Here are the high-level steps you will follow in the course.
- Configure the development environment
- Getting started with AWS
- Storage – Everything about AWS s3 (Simple Storage Service)
- User-Level Security – Managing Users, Roles, and Policies Using IAM
- Infrastructure – AWS EC2 (Elastic Cloud Compute)
- Ingesting Data Using AWS Lambda Functions
- Overview of AWS Glue Components
- Configure Spark History Server for AWS Glue Jobs
- Dive into the AWS Glue catalog
- Explore the AWS Glue Job APIs
- AWS Glue Job Bookmarks
- Pyspark development lifecycle
- Getting started with AWS EMR
- Deploying Spark applications using AWS EMR
- Streaming pipeline using AWS Kinesis
- Consume data from AWS s3 using boto3 ingested using AWS Kinesis
- Populate GitHub data to AWS Dynamodb
- Overview of 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 the AWS Redshift cluster
- AWS Redshift Tables with Distkeys and Sortkeys
- Federated Queries and AWS Redshift Spectrum
Who should attend ?
- Beginner 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 looking to learn Databricks to test data engineering applications built using AWS Analytics Services
What will you learn in Data Engineering Master Class Using AWS Analytics Services Course ,
- Data engineering leveraging AWS Analytics capabilities
- AWS Essentials such as s3, IAM, EC2, etc.
- Understanding AWS s3 for Cloud-Based Storage
- Understand the details related to virtual machines on AWS known as EC2
- Managing AWS IAM Users, Groups, Roles, and Policies for Role Based Access Control (RBAC)
- Managing Tables Using the AWS Glue Catalog
- Batch Data Pipeline Engineering Using AWS Glue Jobs
- Orchestrating batch data pipelines using AWS Glue workflows
- Running Queries Using AWS Athena – Serverless Query Engine Service
- Using AWS Elastic Map Reduction (EMR) Clusters to Create Data Pipelines
- Using AWS Elastic Map Reduction (EMR) Clusters for Reporting and Dashboards
- Ingesting Data Using AWS Lambda Functions
- And…..
Course details:
Editor: Udemy
Instructor: Durga Viswanatha Raju Gadiraju,Asasri Manthena,Perraju Vegiraju
French language
Training level: Advanced
Number of courses: 434
Training duration: 26 hours 15 minutes
Master Class on Data Engineering Using AWS Analytics Services Course Content:
Requirements:
- Programming experience with Python
- Experience in data engineering with Spark
- Ability to write and interpret SQL queries
- This course is ideal for experienced data engineers looking to add AWS Analytics Services as a key skill set to their profile.
Pictures:
Simple video:
installation guide ,
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Subtitle: English
Quality: 720p
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9.12 GB