Modern Data Architecture Hands-on Workshop

Modern Data Architectures Workshop

The Modern Data Architecture Workshop provides you with hands-on experience with the key principles of a modern data architecture on AWS (Purpose Built Services, Unified Governance, Scalable Data Lakes, Seamless Data Movement and Performant and Cost Effective) and is designed to help us accelerate your journey with analytics on AWS. AWS Accounts will be provided on the day, all you need to bring is a laptop and charger!

This workshop has a particular focus on demonstrating :

• How Lake Formation can be used to deliver a scalable, secure and governance data lake.
• A wide range of purpose built services around the data lake, and how / why these should be used.
• Services and best practices for seamlessly moving data Inside Out, Outside in and Around the Perimeter in a Lake House.
• Best practices for performance and cost in the Lake House platform.

The workshop does not rely on any previous knowledge of AWS data analytics

Agenda
The current outline for the labs that will be carried out on the day with timings is set out below. The aim of the day is to give people maximum hands-on time with the various AWS services. There will be time throughout to network and takes breaks, and the workshop will be run in a welcoming and informal manner.

09:30 - Welcome and Modern Data Architecture Overview
Provides context to why the Modern Data Architecture, explains what it is, and explains the key principles
10:00 - Scalable Data Lakes
Focuses on the Data Lake and the key services that enable a well governed, scalable and secure data lake
10:30 - Setting up the Data Lake
Set up the data lake
11:00 - Fine Grained Access Control - Column
Column level permissions in Lake Formation
11:20 - Break
11:35 - Seamless Data Movement
Covers services designed for moving data around a modern data platform, to ensure seamless data movement Outside In, Inside Out and Around the Perimeter
12:20 - Change Data Capture (CDC) From Relational Databases
Change data capture from Aurora to S3
12:40 - Streaming Data Ingestion
Use Amazon Kinesis Data Stream and Data Firehose to deliver changes from DynamoDB to S3 in near real time.
13:00 - Lunch
13:45 - Purpose Built Analytics Services
Walks through various services around the perimeter of a modern data platform, what each does and when customers should choose to use them
14:30 - Log Analytics with OpenSearch
Demonstrates the search use case for OpenSearch in a modern data platform
15:00 - Search data with an OpenSearch API
Creates a searchable product catalog for an API in OpenSearch
15:30 - Data Movement Patterns
Lists a lot of different patterns and technique for moving data in a modern data platform.
16:00 - Query with Amazon Redshift
Load data into Redshift, perform an aggregation query, unload the data back to S3, query with Redshift Spectrum, and query Aurora with Redshift federated query
16:30 - Close