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Amazon Web Services: Data Analytics

via LinkedIn Learning

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Details

Go to class

Provider

LinkedIn Learning
Pricing

Free Trial Available
Languages

English
Certificate

Certificate Available
Duration & workload

2-3 hours
Sessions

On-Demand

Found in

Part of

Advance Your Skills in Predictive Analytics

Overview

Learn about best practices, patterns, and tools for designing and implementing data analytics using AWS.

Syllabus

Introduction

Welcome
Exercise files
About using cloud services

1. Analytics on AWS

AWS analytics design concepts
Files vs. databases
Business vs. predictive analytics
Batching vs. streaming
Which analytics type to use
Data hygiene and ETL
Visualization and QuickSight
QuickSight demo

2. Analytic Services

Setup for AWS analytics
Query Athena using SQL query on S3
Query DynamoDB for NoSQL
Set up Kinesis for input streams
Query Kinesis Analytics
Query CloudSearch and Elasticsearch
Query AWS IoT
Set up EMR, RDS, and Redshift
Query RDS with ANSI SQL
Query Redshift for RDBMS
Query Redshift Spectrum
Query EMR with Apache Spark

3. AWS Code Tools for Analytics

Set up AWS CLI for analytics
Query Athena using the AWS CLI
Query DynamoDB using the AWS CLI
Code tools for analytics
Use the AWS SDK for querying DynamoDB
Using AWS Cloud9

4. Advanced Analytics

Query AWS public datasets
Use AWS Glue for ETL
Understanding ETL options
Use AWS QuickSight for visualizations
Use the AWS Marketplace for visualization tools
Summary of tools
Common analytics architecture patterns

Conclusion

Next steps

Taught by

Lynn Langit

Reviews

4.7 rating at LinkedIn Learning based on 193 ratings

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