Interactive Simulation
Experience What
I Do
Instead of just telling you about data pipelines, try this interactive ETL simulation.
Extract → Transform → Load. In under 3 minutes.
storage
Extract
Database / API
settings
Transform
Filter / Clean
warehouse
Load
Warehouse / Cache
Pipeline Sequence
Stage 01/03
STEP_01
Extract
STEP_02
Transform
STEP_03
Load
Extraction Zone
Select 2+ data sources to initialize the pipeline.
0 sources selected
INCOMING DATA PREVIEW
[STREAM] REST_API → batch_001 { "id": "USR_001", "name": "Alex Carter", email": null, "ts": "2024-01-15T08:22:01Z" } { "id": "USR_002", "name": "Sarah Miller", "email": "sarah@data.io", "ts": "2024-01-15T08:22:05Z" } { "id": "USR_001", "name": "alex carter", /* DUPLICATE */ "email": "alex@data.io" } [STREAM] SQL_DB → snapshot_v2 SELECT * FROM users WHERE region = 'APAC'; ERROR: last_login = "undefined" -- row 412 MISSING_FIELD: status -- row 2091 [STREAM] KAFKA → realtime_events { "event": "purchase", "amount": 142.50, "currency": "USD", "user_id": "USR_042" } { "event": "purchase", "amount": 142.50, /* DUPLICATE */ "user_id": "USR_042" } { "event": "login", "timestamp": "NaN", "user_id": "USR_099" }
error 23 errors detected
content_copy 7 duplicates
format_color_fill 4 null fields
terminal
Data Buffer: Stage_2.RAW
[SCHEMA_ERROR] { "id": "USR_001", "name": "Alex Carter", email: null, "ts": "2024-01-15T08:22:01Z" } [DUPLICATE] { "id": "USR_001", "name": "alex carter", "email": "alex@data.io" } [OK] { "id": "USR_002", "name": "Sarah Miller", "email": "sarah@data.io", "ts": "2024-01-15T08:22:05Z" } [MISSING_FIELD] { "id": "USR_003", "name": "Jason Bourne", "ts": "2024-01-15T09:00:00Z" } [BAD_VALUE] { "event": "login", timestamp: "NaN", "user_id": "USR_099" } [DUPLICATE] { "event": "purchase", "amount": 142.50, "user_id": "USR_042" }
Transform Progress
radio_button_unchecked
Deduplication
Remove 7 duplicate records
radio_button_unchecked
Null Handling
Fill/drop 4 null fields
radio_button_unchecked
Filters Applied
Remove bad timestamps, invalid values
radio_button_unchecked
Schema Normalized
Standardize fields and casing
Data Quality Score
0%
Apply all transforms for 100%
Live Record Count
—
Pipeline Operation
STAGE 03: THE LOAD
Current Throughput
840 GB/s
cleaning_services
Cleaned Stream
hub
Select Target...
Terminal: Ingestion_Log_v2.04
[INFO] Cleaned dataset ready: 1,892 records
[INFO] Schema validation: PASSED
[READY] Awaiting target warehouse selection...
military_tech
verified
Final Rank
Senior Data
Engineer
Operation Successful
Pipeline Performance Report
You just built a data pipeline. This is what I do at scale — processing billions of records with real-time fault tolerance.
Score
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Speed
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