Quick Start Guide

Welcome to Luminal Analytics! This guide will help you get started with our platform in just a few minutes.

Prerequisites

Before you begin, make sure you have:

• A Luminal Analytics account (sign up at luminalanalytics.com)
• Your API key (available in your dashboard)
• Basic knowledge of REST APIs or SQL

Step 1: Authentication

First, you'll need to authenticate with our API. We support several authentication methods:

API Key Authentication

curl -H "Authorization: Bearer YOUR_API_KEY" \
  https://api.luminalanalytics.com/v1/datasets

OAuth 2.0

For web applications, we recommend using OAuth 2.0. Here's how to get started:

const auth = new LuminalAuth({
  clientId: 'your-client-id',
  redirectUri: 'https://yourapp.com/callback',
});

auth.authorize();

Step 2: Upload Your First Dataset

Once authenticated, you can start uploading data:

const dataset = await luminal.datasets.create({
  name: 'My Sales Data',
  description: 'Monthly sales figures',
  data: csvData,
});

Step 3: Create Your First Analysis

Now let's create a simple analysis:

const analysis = await luminal.analyses.create({
  datasetId: dataset.id,
  query: {
    groupBy: ['month'],
    aggregates: {
      total_sales: { field: 'sales', function: 'sum' },
    },
  },
});

Step 4: Visualize Your Data

Finally, create a chart to visualize your results:

const chart = await luminal.charts.create({
  analysisId: analysis.id,
  type: 'line',
  options: {
    xAxis: 'month',
    yAxis: 'total_sales',
    title: 'Monthly Sales Trend',
  },
});

Next Steps

Congratulations! You've successfully:

• ✅ Authenticated with Luminal Analytics
• ✅ Uploaded your first dataset
• ✅ Created an analysis
• ✅ Generated a visualization

What's Next?

• Explore our API Reference for more advanced features
• Learn about Machine Learning capabilities
• Create Interactive Dashboards
• Set up Webhooks for real-time notifications

Need Help?

If you run into any issues:

• Check our FAQ section
• Join our Community Forum
• Contact our Support Team

---

Estimated completion time: 5-10 minutes