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End-to-end batch and streaming data pipeline on AWS to process user ratings and activity data. Leverages Amazon RDS, Glue, S3, Kinesis, and PostgreSQL with pgvector for real-time recommendation generation and model training.
Describes the concepts of lambda architecture and the actual deployment process with an example of building a serverless business intelligence systems using Amazon Kinesis, S3, Athena, OpenSearch Service, and QuickSight.
This Big Data project consists of obtaining data on vehicle theft in the city of São Paulo and consolidating it in a counting and heat map, in order to show areas with a higher index of this type of crime. All applicable in AWS Resources.
Ingestion of bid requests through Amazon Kinesis Firehose and Kinesis Data Analytics. Data lake storage with Amazon S3. Restitution with Amazon QuickSight and CloudWatch. 📉