Data Analytics on AWS

Course Overview

Chapter 1 - The AWS Lake Formation Service

• First, What is a Data Lake?
• Data Lakes vs Traditional Data Warehouses
• Characteristics of Data Warehouses and Data Lakes
• Now, What is AWS Lake Formation?
• What are the Benefits of Using Lake Formation?.
• How Lake Formation Works.
• The Lake Formation Dashboard.
• AWS Lake Formation Pricing

Chapter 2 - AWS Simple Storage Service

• What is AWS Simple Storage Service (S3).
• AWS Storage.
• Regions
• S3 Regions.
• Getting started with S3.
• Using BitTorrent
• More on Buckets.
• Bucket Configurable Properties.
• Advanced S3 Bucket Properties.
• The Bucket Creation Dialog in the Management Console.
• Bucket Permissions.
• Bucket-level Operations.
• Authorization of REST Requests.
• Adding Cross-Origin Resource Sharing Configuration
• Event Notifications.
• The Requester Pays Option.
• The Object Key
• Object Versioning.
• Example of Object Properties
• Object Storage Class Levels.
• Object-level Operations.
• Object Lifecycle Configuration.
• Amazon S3 Data Consistency Model
• Observable Data Consistency Behaviors
• Eventually Consistent Reads vs Consistent Reads.
• Amazon S3 Security.
• S3 Use Case: Backup and Archiving.
• Another S3 Use Case: Static Web Hosting
• More on Static Web Hosting.
• S3 Static Website Hosting Dialog in Management Console.
• S3 Use Case: Disaster Recovery
• AWS S3 Pricing
• Storage Pricing.  
• Request Pricing.
• Data Transfer Pricing.
• Amazon S3 Transfer Acceleration.
• How to Enable Transfer Acceleration
• Enabling Transfer Acceleration in the Management Console.
• Amazon S3 SLA Definitions
• Amazon S3 SLA Service Commitment
• S3 CLT
• Summary

Chapter 3 - Redshift.

• Overview.
• Terms
• Data Warehouse.
• Traditional Extract Transform Load (ETL)
• Data Lake.
• Database
• Redshift Features.
• High Performance.
• Simple Management.
• Cost-effective.
• Elasticity
• Query your Data Lake.
• Security.
• Partners Offer Certified Solutions
• Data Warehouse Challenges.
• Redshift Spectrum.
• As islWhere is Data.
• Scalability with Redshift Spectrum
• Combine data warehouse and the data lake.
• SQL Queries across S3 and Redshift.
• Redshift Query
• Summary

Chapter 4 - Redshift Optimizations

• Queues.
• Superuser Queue.
• Default Queues.
• User Defined Queues.
• Workload Management (WLM)
• Concurrency level.
• User groups
• Query groups.
• Memory %
• Timeout.
• Sort keys.
• Compound Sort Keys.
• Tnterleaved Sort Keys.
• Cleaning Up Data
• Summary

Chapter 5 - Visualization and Reporting.

• Amazon QuickSight.
• SPTCE.
• Data Analyses.
• Visuals.
• Sheets
• Stories.
• Dashboards.
• Typical Amazon QuickSight Workflow
• Create a Data Set
• Create an Analysis.
• Create a Visual Manually.
• Amazon Athena.
• Amazon Athena and AWS Data Catalog.
• Query Data Using Amazon Athena.
• Create a Report Using Tablea
• Create a Report Using Tableau (Contd.).
• Summary

Chapter 6 - Tntroduction to AWS Glue

• What is AWS Glue?.
• AWS Glue Components.
• AWS Glue Components (Cont'd).
• AWS Glue Components (Cont'd).
• Managing Notebooks
• AWS Glue Components (Cont'd).
• Putting it Together: The AWS Glue Environment Architecture
• AWS Glue Main Activities
• Additional Glue Services
• When To Use AWS Glue?
• Tntegration with other AWS Services.
• Summary

Chapter 7 - AWS Glue PySpark Extensions.

• AWS Glue and Spark.
• The DynamicFrame Object
• The DynamicFrame APT.
• The GlueContext Object.
• Glue Transforms.
• A Sample Glue PySpark Script.
• Using PySpark
• AWS Glue PySpark SDK.

Summary

Prerequisites

Participants must have a general knowledge of a modern programming language.