Automated Data Analytics on AWS

Visualize your cloud data workflows with the Automated Data Analysis on AWS example.

Automated Data Analytics on AWS

Visualize your cloud data workflows with the Automated Data Analysis on AWS example.

Architecture Diagrams
Diagram-as-code
AWS
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about this example

AWS is central to modern cloud architectures, and this example provides a comprehensive overview of a robust data analysis setup. Here’s a breakdown of the example:

  • Ingress (Data Connectors): Shows various data sources like JSON and CSV files, AWS services (S3, DynamoDB), and Google services (Analytics, BigQuery).
  • Automated Data Analysis on AWS: Details the process flow from source connectors through ETL (AWS Glue) to data product creation.
  • Core Services: Outlines governance, query services, and notification mechanisms required for a secure and efficient data analysis environment.
  • Frontend and Egress: Illustrates how data is presented to end-users via tools like Power BI, and how it interacts with front-end services like static websites and APIs.
When to use
  • Data Workflow Design: When structuring a cloud-based data pipeline that requires coordination of various AWS services and external data sources.
  • Compliance and Governance: When your team needs to understand and implement data governance and compliance within AWS.
  • Educational Resource: When onboarding new team members to the AWS ecosystem, this diagram can serve as a visual aid for understanding the data flow and services involved.
How to use
  1. Start editing: Duplicate example file and double-click on the diagram.
  2. Customize diagram: Add / modify nodes, groups, relationships using your chosen diagram-as-code syntax. Use icons where possible to make the diagram more intuitive.
  3. Customize layout: Drag elements on the diagram directly on the canvas to manipulate the layout.
  4. Collect feedback: Share the file with collaborators and encourage them to use the comments feature for feedback.

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