Data Engineering Guide

Data Architecture Diagram Generator

Document your data platform with diagrams that show responsibilities, controls, and interfaces. Generate them fast, then keep them versioned like code.

Generate an architectureSee AWS architecture guide
12 min readArchitecture-first promptsGovernance checklist included

See it as a diagram

Start from one of the prompts below — edit it and generate.

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No account needed · Editable canvas, not a picture

Why architecture diagrams still win reviews

Architecture diagrams communicate boundaries and responsibilities faster than docs. They make design reviews, SOC2 evidence, and onboarding smoother.

Keep them focused on contracts: what enters, what leaves, who owns each boundary.

Shared understanding

Engineers, analysts, and security see the same map.

Decision history

Capture trade-offs (batch vs streaming, lakehouse vs warehouse).

Audit ready

Highlight encryption, retention, and access controls.

Repeatable exports

Keep JSON + SVG/PNG so updates are painless.

Foundations of a solid architecture diagram

A good diagram shows domains, layers, and contracts. Avoid clutter by grouping related services and showing only critical paths.

  • Domains across the top (marketing, product, finance) with owning teams.
  • Layers: sources, ingest, storage (raw/refined/curated), processing, serving.
  • Contracts on edges: protocol, schedule, retention, failure behavior.
  • Non-functional needs: latency targets, compliance zones, cost boundaries.
  • Observability: where logs, metrics, and traces are emitted.

Governance and risk cues to include

Architecture diagrams should answer security and compliance questions without another meeting.

PII and PCI markers

Mark where sensitive data lands and how it is protected.

Access boundaries

Show IAM roles, VPC boundaries, and row-level security.

Lineage hooks

Note where lineage is captured for audits.

Retention and backup

Call out retention policies and disaster recovery paths.

Workflow to keep it accurate

Regenerate from prompts tied to your inventory, review once, and publish everywhere the team works.

Simple loop

  • • Generate from current systems and contracts.
  • • Review owners, SLAs, and governance markers.
  • • Export SVG/PNG and store JSON in git for diffs.
  • • Publish to wiki and link from runbooks with a date.

Prompts for architecture diagrams

Create a data architecture diagram with domains marketing/product/finance. Show sources (Salesforce, app DB), ingest (Fivetran, Kafka), storage (S3 raw/refined/curated), processing (dbt on Snowflake), serving (Looker, reverse ETL). Add owners and SLAs.
Generate a secure architecture: inbound APIs -> ingestion (Kafka) -> lakehouse (Delta Lake bronze/silver/gold) -> Databricks jobs -> warehouse (Unity Catalog) -> BI and ML features. Highlight encryption, access roles, and retention.
Draw a platform diagram for real-time analytics: CDC -> Kafka -> Flink -> ClickHouse serving + Snowflake for history. Include monitoring and backup paths.
Produce an audit-friendly diagram marking PII zones, row-level security, and where lineage is captured.

Publish checklist

All systems and domains match production names.
Edges show contracts (protocol, schedule, retention).
Security markers (PII, RLS, encryption) are present.
Exports: JSON for diffing, SVG for decks, PNG for quick sharing.
Date and reviewer noted in the wiki entry.

FAQ

How is an architecture diagram different from a flow diagram?

Architecture diagrams show components, boundaries, and responsibilities. Flow diagrams emphasize the movement of data. Use both: architecture for design reviews, flow for operations.

What layers must appear on a data architecture diagram?

Sources, ingestion, storage zones (raw/refined/curated), processing engines, serving layers, governance and security controls, and observability.

How do I keep architecture diagrams current?

Regenerate from prompts tied to your latest inventory, store the JSON source in git, and set a quarterly review. Avoid editing one-off slides that drift.

Can I include cloud resources?

Yes. Reference specific services (S3, BigQuery, Databricks, Snowflake, Kafka) and note regions, encryption, and network boundaries.

Generate architecture diagrams your team trusts

Use AI plus a repeatable checklist to keep diagrams aligned with what runs in production.

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