CloudSketch AI Logo
FeaturesTemplatesPricingEnterpriseAboutContactLog in
πŸŒ™β˜€οΈ
Log inStart free
Home/Templates/Data Engineering & Analytics

πŸ“Š Data Engineering & Analytics Β· Data Flow

Data Lake Zones (Bronze, Silver, Gold)

The medallion pattern for a data lake: raw data lands in bronze, is cleaned in silver, and turned into business-ready tables in gold.

More Data Engineering & Analytics templates

Drawing diagram…

What this diagram shows

  • Bronze keeps raw data exactly as received
  • Silver removes duplicates and fixes types
  • Gold holds aggregated tables for reports and ML

Prompt used

Medallion architecture data flow: batch files, API data and streaming events land unchanged in the bronze zone of a Delta Lake. A cleaning job de-duplicates, standardises types and masks personal data into silver. Aggregation jobs build gold tables such as daily revenue and customer 360. BI tools and ML features read from gold.

Mermaid code
flowchart LR
  F[Batch Files] -->|As received| BR[(Bronze Zone)]
  API[Partner APIs] -->|JSON| BR
  EV[Event Stream] -->|Events| BR
  BR -->|Raw records| CL[Cleaning Job]
  CL -->|De-duplicated, typed, masked| SV[(Silver Zone)]
  SV -->|Clean tables| AG[Aggregation Jobs]
  AG -->|Daily revenue, customer 360| GD[(Gold Zone)]
  GD -->|Metrics| BI[BI Dashboards]
  GD -->|Features| ML[ML Training]

Related templates

C4 ArchitectureProData Engineering & Analytics

Modern Data Platform Architecture

A typical modern data stack: data is loaded from apps and SaaS tools into a cloud warehouse, modelled with dbt, orchestrated with Airflow and served to BI dashboards.

Data FlowData Engineering & Analytics

Change Data Capture Pipeline

How every insert, update and delete in an operational database is streamed to the data lake and search index in near real time using change data capture.

Database ERDData Engineering & Analytics

Sales Star Schema

A classic star schema for sales analytics: one fact table of order lines surrounded by date, customer, product, store and promotion dimensions.

FlowchartData Engineering & Analytics

Nightly Batch ETL Workflow

The steps of a nightly batch pipeline with data quality gates: extract, validate, transform, load and publish, stopping safely when checks fail.

DeploymentProData Engineering & Analytics

Real-time Streaming Analytics Deployment

Where a real-time analytics stack runs: Kafka for events, Flink for stream processing, a real-time OLAP database and live dashboards.

State MachineData Engineering & Analytics

Data Pipeline Run States

The states of a single pipeline run in an orchestrator like Airflow, including retries, upstream failures and manual reruns.