ABT Analytics Dashboard

High-performance analytics dashboard for ABT Corporation's transaction data. Built with Go backend, React frontend, and powered by DuckDB for blazing-fast SQL analytics.

Author: Randil Tharusha

Features

• Country-level revenue analysis with transaction counts and pagination
• Top 20 most purchased products with stock levels
• Monthly sales volume trends with date-based aggregation
• Top 30 regions by revenue and items sold
• Blazing-fast SQL queries using DuckDB's columnar storage
• Real-time analytics with automatic CSV loading
• Concurrent data processing for optimal performance
• Memory-efficient in-memory database with instant queries

Tech Stack

• Backend: Go 1.24
• Frontend: React + Vite
• Database: DuckDB (in-memory columnar analytics)
• Data Processing: SQL-powered queries
• Containerization: Docker + Docker Compose

Prerequisites

• Go 1.24 or later
• Node.js 18 or later
• npm or yarn
• Make (optional, for using make commands)

Dataset Setup

The repository includes dummy data files for reference:

• data/raw/transactions.csv (100 rows - 99 records + 1 header)

These files are for reference only. Before running the application:

1. Remove the dummy files:

rm data/raw/transactions.csv

2. Place your full transaction dataset in data/raw/transactions.csv

Note: DuckDB can handle datasets of any size efficiently thanks to its columnar storage and SQL optimization.

Setup

Quick Start Script ⚡

Use start.sh script that automates the setup and startup process:

# Make the script executable
chmod +x start.sh

# Run the script
./start.sh

The script will:

1. Install backend dependencies
2. Build the backend
3. Install frontend dependencies
4. Build the frontend
5. Start both services

Manual Setup

1. Clone the repository:

git clone https://github.com/randilt/abt-corp-analytics-dashboard.git
cd abt-corp-analytics-dashboard

2. Backend Setup:

# Install Go dependencies
go mod download

# Build the backend
go build -o bin/server cmd/server/main.go

# Run the backend
./bin/server

3. Frontend Setup:

cd web
npm install
npm run build
npm run preview

Docker Setup

Pull from dockerhub:

docker pull randilt/abt-corp-analytics-dashboard:latest

Or start with docker-compose:

docker-compose up -d

Configuration

The application can be configured using environment variables:

Server Configuration

SERVER_HOST=localhost          # Server hostname
SERVER_PORT=8080              # Server port
SERVER_READ_TIMEOUT=15s       # Read timeout
SERVER_WRITE_TIMEOUT=15s      # Write timeout
SERVER_IDLE_TIMEOUT=60s       # Idle timeout

CSV Configuration

CSV_FILE_PATH=./data/raw/transactions.csv  # Path to CSV file

Logging Configuration

LOG_LEVEL=info               # Log level (debug, info, warn, error)

Example usage:

# Run with custom configuration
CSV_FILE_PATH=./my-data.csv ./bin/server

Accessing the Dashboard

• Frontend: http://localhost:4173
• Backend API: http://localhost:8080/api/v1

Data Processing

• DuckDB Integration: CSV data is loaded directly into DuckDB's in-memory columnar database
• SQL-Powered Analytics: All analytics are generated using optimized SQL queries
• Automatic Loading: Data is loaded fresh on every application startup
• Memory Efficient: Only loads data as needed for each query
• Real-time: No caching needed - queries are always fresh and fast

API Endpoints

• GET /api/v1/analytics - Get all analytics data summary
• GET /api/v1/analytics/stats - Get analytics statistics
• GET /api/v1/analytics/country-revenue?limit=100&offset=0 - Country revenue data with pagination
• GET /api/v1/analytics/top-products - Top 20 products
• GET /api/v1/analytics/monthly-sales - Monthly sales trends
• GET /api/v1/analytics/top-regions - Top 30 regions
• POST /api/v1/analytics/refresh - Force data reload
• GET /health - Health check
• GET /ready - Readiness check

Performance

• CSV Loading: ~25ms for 99 records
• Query Performance: Sub-millisecond response times
• Memory Usage: Minimal - only loads what's needed
• Scalability: Handles datasets of any size efficiently
• Concurrent Queries: All analytics generated in parallel

Why DuckDB?

• Columnar Storage: Optimized for analytical workloads
• SQL Interface: Familiar and powerful query language
• Memory Efficient: Only loads necessary data
• Blazing Fast: Sub-second queries on large datasets
• No External Dependencies: Embedded database, no server needed
• CSV Native: Direct CSV loading without preprocessing

Testing

# Run all tests
make test

# Generate coverage report
make test-coverage

# Generate detailed coverage report
make test-coverage-detailed

The coverage report will be generated in ./coverage/coverage.html. Open this file in your browser to view:

• Line-by-line coverage
• Function coverage
• Overall coverage statistics

Note: Coverage report is generated even if some tests fail.

Troubleshooting

1. If data isn't loading:

   • Check if the backend is running (curl http://localhost:8080/health)
   • Verify the CSV file exists in data/raw/transactions.csv
   • Check server logs for DuckDB initialization errors

2. If the frontend build fails:

   • Clear node_modules and reinstall: rm -rf node_modules && npm install
   • Ensure you're using Node.js 18 or later

3. If queries are slow:

   • Check CSV file format and column names
   • Verify data types are correct (dates, numbers)
   • Check server logs for SQL errors

Architecture

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   React Frontend │    │   Go Backend     │    │   DuckDB        │
│                 │    │                  │    │                 │
│ - Dashboard UI  │◄──►│ - REST API       │◄──►│ - In-memory DB  │
│ - Charts        │    │ - Handlers       │    │ - SQL Queries   │
│ - Real-time     │    │ - Middleware     │    │ - Columnar      │
└─────────────────┘    └──────────────────┘    └─────────────────┘
                                │
                                ▼
                       ┌──────────────────┐
                       │   CSV File       │
                       │                  │
                       │ - transactions   │
                       │ - Auto-loaded    │
                       └──────────────────┘