AWS Certified Big Data Specialty 2020 - In Depth & Hands On!
Service Will Learn
Introducing our Hands-On Case Study: Cadabra.com
Requirement 1: Order history app
- site's mobile app to do this will simulate order data being generated on an easy to instance and publish that data
- Data using Kinesis data streams into an AWS lambda function which in turn will populate an order database in dynamoDB that our app can read from.
Requirement 2: Product recommendations
Automated product recommendations to our customers online which involves training a machine learning:
- Model based on aggregate customer purchasing data to build this we'll publish our order data through Kinesis firehose into a data lake hosted in Amazon S3
- spin up an Amazon Elastic map reduce cluster to produce recommendations model using Apache Spark.
Requirement 3: Transaction rate alarm
Next we'll create an operational system that alerts us if an unexpected rate of orders comes in all of a sudden. This might indicate some sort of attack that someone needs to deal with immediately.
- And so it must work in real time to build this will use Kinesis data streams and Kinesis data analytics to monitor our incoming orders
- Use a lambda function to fire off alarms using Amazon SNS or cell phone when something unusual happens.
Requirement 4: Near-real-time log analysis
We also want to be able to analyze server log data in near real time for operational purposes for this requirement.
- We'll use Kinesis firehose to pump Apache log data directly into the Amazon Elastic search service
Requirement 5: Data warehousing & visualization
Final: Put it together
