🏗️ NodeQ MindMap Architecture
System Architecture Overview
graph TB
subgraph "🎨 Visualization Layer"
A[Interactive Mind Maps]
B[Pipeline Monitoring]
C[Performance Dashboards]
end
subgraph "🧠 ML Analysis Engine"
D[TensorFlow.js Model]
E[Hugging Face Integration]
F[OpenAI API Support]
G[Pattern Recognition]
H[Field Mapping Intelligence]
end
subgraph "⚙️ Pipeline Engine"
I[ETL Process Automation]
J[Stream Processing]
K[Data Quality Validation]
L[Error Handling]
end
subgraph "🔌 Data Source Connectors"
M[IoT Hub]
N[Kafka]
O[REST APIs]
P[WebSockets]
Q[MQTT]
R[Databases]
end
A --> D
B --> I
C --> J
D --> I
E --> G
F --> H
G --> I
H --> J
M --> I
N --> J
O --> I
P --> J
Q --> I
R --> I
ETL Process Flow
graph LR
subgraph "Data Input"
A[IoT Sensors]
B[Kafka Streams]
C[REST APIs]
D[Databases]
end
E[Data Extraction] --> F[Auto Schema Detection]
F --> G[ML Pattern Analysis]
G --> H[Rule Generation]
H --> I[Data Transformation]
I --> J[Quality Validation]
J --> K[Error Handling]
K --> L[Output Processing]
subgraph "Data Output"
M[Analytics DB]
N[Real-time Dashboard]
O[Alert Systems]
P[ML Training Data]
end
A --> E
B --> E
C --> E
D --> E
L --> M
L --> N
L --> O
L --> P
ML Model Interaction Lifecycle
sequenceDiagram
participant User as User
participant NodeQ as NodeQ Engine
participant ML as ML Model
participant Pipeline as Compiled Pipeline
participant Data as Input Data
Note over User,Data: Pipeline Creation Phase (ML Active)
User->>NodeQ: Create Pipeline (input/output samples)
NodeQ->>ML: Initialize Model
ML->>ML: Analyze transformation patterns
ML->>NodeQ: Generate transformation rules
NodeQ->>Pipeline: Compile static execution logic
NodeQ->>User: Pipeline ready (ML model no longer needed)
Note over User,Data: Execution Phase (Static, ML-Free)
Data->>Pipeline: Input data
Pipeline->>Pipeline: Execute compiled transformations
Pipeline->>User: Transformed output (fast, no ML overhead)
Note over User,Data: Configuration Update Phase (ML Re-activated)
User->>NodeQ: Update pipeline config
NodeQ->>ML: Re-initialize model
Real-World Pipeline Examples
E-commerce Data Pipeline
flowchart TB
subgraph "E-commerce Data Sources"
A[📦 Order Management<br/>System]
B[📊 Inventory Database<br/>PostgreSQL]
C[👥 Customer CRM<br/>Salesforce]
D[💳 Payment Gateway<br/>Stripe/PayPal]
E[🚚 Shipping Provider<br/>FedEx/UPS API]
end
subgraph "NodeQ Smart Pipeline"
F[📥 Data Ingestion<br/>Multi-source Connector]
G[🔍 Auto Schema Detection<br/>JSON/SQL Analysis]
H[🧠 ML Pattern Analysis<br/>TensorFlow.js]
I[⚡ Rule Generation<br/>Auto Transformation]
J[✅ Quality Validation<br/>Error Detection]
end
subgraph "Business Intelligence"
K[📈 Analytics Database<br/>Snowflake/BigQuery]
L[📊 Real-time Dashboard<br/>Revenue Metrics]
M[🎯 ML Training Data<br/>Customer Insights]
N[🚨 Alert System<br/>Inventory/Fraud]
end
A --> F
B --> F
C --> F
D --> F
E --> F
F --> G
G --> H
H --> I
I --> J
J --> K
J --> L
J --> M
J --> N
Financial Data Aggregation
flowchart TB
subgraph "Market Data Sources"
A[📈 Stock Market APIs<br/>Yahoo Finance, Alpha Vantage]
B[₿ Crypto Exchanges<br/>Binance, Coinbase Pro]
C[💱 Forex Data Feeds<br/>OANDA, XE]
D[📰 Financial News APIs<br/>Bloomberg, Reuters]
E[📊 Economic Indicators<br/>Fed, ECB, World Bank]
end
subgraph "NodeQ Financial ETL"
F[⚡ Real-time Ingestion<br/>WebSocket + REST]
G[🧠 ML Price Analysis<br/>Pattern Recognition]
H[⚖️ Risk Calculations<br/>VaR, Beta, Correlation]
I[✅ Compliance Checks<br/>Regulatory Validation]
J[🔄 Data Normalization<br/>Currency, Time Zones]
end
subgraph "Trading & Risk Systems"
K[💼 Trading Platform<br/>Order Management]
L[🎯 Risk Dashboard<br/>Portfolio Monitoring]
M[📋 Regulatory Reports<br/>MiFID II, Dodd-Frank]
N[📊 Analytics Engine<br/>Backtesting, Modeling]
end
A -.->|High Freq| F
B -.->|Real-time| F
C -.->|Streaming| F
D -.->|Event-driven| F
E -.->|Scheduled| F
F --> G
G --> H
H --> I
I --> J
J --> K
J --> L
J --> M
J --> N
IoT Manufacturing Pipeline
flowchart TB
subgraph "Factory Floor Sensors"
A[🌡️ Temperature Sensors<br/>Production Lines 1-5]
B[🔧 Pressure Gauges<br/>Hydraulic Systems]
C[📳 Vibration Monitors<br/>Motor Assemblies]
D[📷 Quality Cameras<br/>Visual Inspection]
E[⚡ Power Meters<br/>Energy Consumption]
end
subgraph "Edge Computing Layer"
F[🖥️ Edge Gateway<br/>Local Processing]
G[🔄 Data Aggregation<br/>Time Series Buffer]
H[📡 Secure Transmission<br/>Factory to Cloud]
end
subgraph "NodeQ Industrial Pipeline"
I[📊 Real-time Ingestion<br/>MQTT/OPC-UA]
J[🧠 ML Anomaly Detection<br/>Pattern Analysis]
K[🔮 Predictive Maintenance<br/>Failure Prediction]
L[✅ Quality Assessment<br/>Defect Detection]
end
subgraph "Enterprise Integration"
M[🏭 MES System<br/>Manufacturing Execution]
N[🔧 CMMS<br/>Maintenance Scheduling]
O[📈 Quality Dashboard<br/>SPC Charts]
P[📱 Mobile Alerts<br/>Operator Notifications]
end
A -->|MQTT| F
B -->|Modbus| F
C -->|Industrial Ethernet| F
D -->|HTTP/REST| F
E -->|OPC-UA| F
F --> G
G --> H
H --> I
I --> J
J --> K
K --> L
L --> M
L --> N
L --> O
L --> P
Component Architecture
Core Components Interaction
graph TB
subgraph "Frontend Components"
A[MindMap Visualization]
B[Pipeline Builder UI]
C[Data Source Configurator]
D[Performance Monitor]
end
subgraph "Core Engine"
E[NodeQ MindMap Engine]
F[Pipeline Compiler]
G[ML Pattern Analyzer]
H[Data Transformer]
end
subgraph "Data Layer"
I[Schema Registry]
J[Pipeline Store]
K[Model Cache]
L[Metrics Store]
end
A --> E
B --> F
C --> E
D --> L
E --> G
F --> H
G --> I
H --> J
G --> K
Data Flow Architecture
graph LR
subgraph "Input Stage"
A[Raw Data Sources]
B[Data Ingestion Layer]
C[Format Detection]
end
subgraph "Processing Stage"
D[Schema Analysis]
E[Pattern Recognition]
F[Transformation Rules]
G[Quality Validation]
end
subgraph "Output Stage"
H[Data Transformation]
I[Format Conversion]
J[Output Delivery]
end
A --> B --> C
C --> D --> E --> F --> G
G --> H --> I --> J