name: bi-builder description: Build BI dashboards from databases. Use when creating dashboards, charts, or analytics pages with Next.js + shadcn/ui + Recharts + Prisma.
BI Builder
Build BI dashboards from existing databases, from data exploration to full implementation.
Tech Stack
| Layer | Technology |
|---|---|
| Frontend Framework | Next.js 16 (App Router) |
| UI Components | shadcn/ui + Tailwind CSS |
| Charts | Recharts |
| ORM | Prisma |
| Database | MySQL / PostgreSQL / Supabase / SQLite |
Core Workflow
Database Connection → Schema Exploration → Requirements Dialog → Metrics Design → Chart Planning → Page Implementation
Workflow Flexibility
Skip phases based on project state and user needs:
| Scenario | Skip Phases | Starting Point |
|---|---|---|
Project has prisma/schema.prisma | Phase 1 | Go directly to Phase 2 schema analysis |
| User has clear requirements and metrics | Phase 3 | Go directly to Phase 4 metrics design |
| Only need a single chart component | Phases 1-5 | Read recharts-guide.md and implement |
| Only need data query logic | Phases 5-6 | End after metrics design |
Decision criteria:
- Check if
prisma/schema.prismaexists in project - Ask user "Do you have specific metrics requirements?"
- Ask user "Do you need a full dashboard or just a single chart?"
Phase 1: Database Connection
1.1 Check and Install Prisma
First, check if Prisma is already installed in the project:
# Check if prisma is in package.json dependencies
grep -q '"prisma"' package.json && echo "Prisma installed" || echo "Prisma not installed"
If Prisma is not installed, install it:
# Install Prisma as dev dependency
npm install prisma --save-dev
# Install Prisma Client
npm install @prisma/client
1.2 Initialize Prisma
# Initialize Prisma (creates prisma/schema.prisma and .env)
npx prisma init
Note: If prisma/schema.prisma already exists, skip this step.
1.3 Create .env with Placeholders
⚠️ Security Note: Never ask users to share database credentials directly.
First, ask user which database type they use, then create .env file with placeholders:
Which database are you using?
1. MySQL
2. PostgreSQL
3. Supabase
4. SQLite
For MySQL:
# Database Connection
# Please fill in your database credentials below
DATABASE_URL="mysql://YOUR_USERNAME:YOUR_PASSWORD@YOUR_HOST:3306/YOUR_DATABASE"
# Example:
# DATABASE_URL="mysql://root:password123@localhost:3306/myapp_db"
For PostgreSQL:
# Database Connection
# Please fill in your database credentials below
DATABASE_URL="postgresql://YOUR_USERNAME:YOUR_PASSWORD@YOUR_HOST:5432/YOUR_DATABASE"
# Example:
# DATABASE_URL="postgresql://postgres:password123@localhost:5432/myapp_db"
For Supabase:
# Supabase Database Connection
# Find your connection string in: Supabase Dashboard → Project Settings → Database → Connection string → URI
DATABASE_URL="postgresql://postgres.YOUR_PROJECT_REF:YOUR_PASSWORD@aws-0-YOUR_REGION.pooler.supabase.com:6543/postgres?pgbouncer=true"
# Direct connection (for migrations)
DIRECT_URL="postgresql://postgres.YOUR_PROJECT_REF:YOUR_PASSWORD@aws-0-YOUR_REGION.pooler.supabase.com:5432/postgres"
# Example:
# DATABASE_URL="postgresql://postgres.abcdefghijkl:MyPassword123@aws-0-us-east-1.pooler.supabase.com:6543/postgres?pgbouncer=true"
For SQLite:
# Database Connection
DATABASE_URL="file:./dev.db"
After creating the file, tell the user:
For MySQL/PostgreSQL:
I've created .env file with placeholders. Please fill in your actual database credentials:
- YOUR_USERNAME → your database username
- YOUR_PASSWORD → your database password
- YOUR_HOST → database host (e.g., localhost or IP address)
- YOUR_DATABASE → database name
Tip: Use a read-only account for safety.
Let me know when you've filled in the credentials.
For Supabase:
I've created .env file with Supabase placeholders. To get your connection string:
1. Go to Supabase Dashboard → Your Project
2. Click "Project Settings" (gear icon)
3. Go to "Database" section
4. Copy the "Connection string" → "URI" format
5. Replace [YOUR-PASSWORD] with your database password
Let me know when you've filled in the credentials.
1.4 Configure Prisma Schema
After user confirms .env is configured, update prisma/schema.prisma:
For MySQL/PostgreSQL/SQLite:
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "mysql" // or postgresql, sqlite
url = env("DATABASE_URL")
}
For Supabase (requires directUrl for migrations):
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
directUrl = env("DIRECT_URL")
}
1.5 Pull Database Schema
# Pull schema from existing database
npx prisma db pull
# Generate Prisma Client
npx prisma generate
1.6 Error Handling
When connection fails:
| Error Message | Possible Cause | Solution |
|---|---|---|
Can't reach database server | Network/Firewall | Check host address and port accessibility |
Access denied | Insufficient permissions | Verify username, password, and user privileges |
Unknown database | Database doesn't exist | Confirm database name spelling |
SSL connection error | SSL configuration | Add ?sslmode=require to DATABASE_URL |
Post-schema pull checks:
- If few tables (< 3) → Confirm connection to correct database
- If no relationships → May be legacy database, need manual relationship analysis
Phase 2: Schema Exploration & Analysis
2.1 Read Generated Schema
After prisma db pull, read prisma/schema.prisma and analyze:
- Table structure: What tables exist, what fields each has
- Data types: Numeric, datetime, categorical fields
- Relationships: Table associations (one-to-many, many-to-many)
- Indexes: Which fields are indexed, indicating common query dimensions
2.2 Identify Metric Potential
Identify buildable metrics by field type:
| Field Type | Metric Potential |
|---|---|
Decimal/Float/Int (amounts, quantities) | Sum, average, max/min |
DateTime | Time series analysis, YoY/MoM comparisons |
Enum/String (status, category) | Group statistics, distribution analysis |
@relation | Join aggregations, multi-dimensional analysis |
Boolean | Conversion rates, completion rates |
2.3 Generate Data Overview Report
Present database overview to user:
## Database Overview
### Core Tables
- **orders** (Orders table): 12 fields, related to users, products
- **users** (Users table): 8 fields
- **products** (Products table): 10 fields, related to categories
### Available Metrics
**Transaction Metrics**
- Total revenue (orders.total)
- Order count (orders.count)
- Average order value (orders.total / orders.count)
**User Metrics**
- Total users (users.count)
- New users (users.created_at)
**Product Metrics**
- Sales ranking (order_items.quantity)
- Category distribution (categories)
### Time Dimensions
- orders.created_at → Supports daily/weekly/monthly analysis
- users.created_at → Supports user growth analysis
Phase 3: Requirements Dialog
3.1 Questioning Strategy
Principle: Ask one question at a time, prefer multiple choice, ask in rounds.
Round 1: Industry Identification (Highest Priority)
Question 0: What industry is your business in?
Options: E-commerce/Retail / SaaS Software / Financial Services / Content/Media / Education / Healthcare / Logistics/Supply Chain / Other
Industry determines metric direction:
| Industry | Core Focus | Typical Metrics |
|---|---|---|
| E-commerce/Retail | Transaction conversion | GMV, AOV, Repeat purchase rate, Return rate, Inventory turnover |
| SaaS Software | User retention | MRR/ARR, Churn Rate, LTV, CAC, DAU/MAU |
| Financial Services | Risk & return | AUM, Bad debt rate, Delinquency rate, Approval rate |
| Content/Media | Traffic monetization | PV/UV, Session duration, Bounce rate, Ad revenue, Paid conversion |
| Education | Learning outcomes | Course completion rate, Renewal rate, Referral rate, Study time |
| Healthcare | Service efficiency | Visit volume, Bed turnover, Return visit rate, Satisfaction |
| Logistics/Supply Chain | Operational efficiency | Order fulfillment rate, Delivery time, Warehouse cost, Turnover rate |
Round 2: Core Metrics Confirmation (Use AskUserQuestion tool)
Based on industry + schema analysis, generate metric options:
Question 1: Based on [industry] context and database analysis, which core metrics matter most to you? (Multiple select)
Options: [Combine industry typical metrics + schema-supported metrics]
Question 2: What's your primary time granularity for analysis?
Options: Daily / Weekly / Monthly / Quarterly
Round 3: Conditional Follow-ups
Only ask when conditions are met:
| Condition | Follow-up |
|---|---|
| Schema has category tables | "Do you need category filtering?" |
| User selected multiple metrics | "Do you need metric comparisons (YoY/MoM)?" |
| Data volume may be large | "Do you need export functionality?" |
Round 4: Confirmation
Show requirements confirmation template, ask "Is the above understanding correct?"
3.2 Data Structure Limitation Handling
When user requirements don't match data, clearly inform:
| User Request | Missing Data | Response |
|---|---|---|
| Regional distribution analysis | No region field | "Database has no region information, cannot implement. Should we analyze by [available dimension] instead?" |
| Trend analysis | No datetime field | "Missing datetime field, can only do static statistics, cannot show trends." |
| User profiling | Limited user fields | "User data is limited, can only track basic metrics (count, new users)." |
3.3 Requirements Confirmation Template
Organize user requirements:
## Requirements Confirmation
### Dashboard Name
Sales Analytics Dashboard
### Core Metrics (KPI Cards)
1. Total Revenue - orders.total sum
2. Order Count - orders count
3. AOV - Total Revenue / Order Count
4. New Users - users count (this month)
### Chart Requirements
| Chart | Type | Data Source | Dimension |
|-------|------|-------------|-----------|
| Revenue Trend | Line Chart | orders.total | By day/month |
| Category Sales | Pie Chart | categories | Category distribution |
| Top 10 Products | Bar Chart | products | Sales ranking |
| Order Status | Pie Chart | orders.status | Status distribution |
### Filters
- Date range picker
- Product category dropdown
- Order status multi-select
### Other Requirements
- CSV export support
- Responsive layout
Phase 4: Metrics Design
4.1 Define Metric Calculation Logic
Based on confirmed requirements, define calculation for each metric:
// lib/metrics.ts
// KPI Metrics
export async function getKPIs(startDate: Date, endDate: Date) {
const [revenue, orders, users] = await Promise.all([
// Total revenue
prisma.order.aggregate({
where: { createdAt: { gte: startDate, lte: endDate }, status: { not: 'CANCELLED' } },
_sum: { total: true },
}),
// Order count
prisma.order.count({
where: { createdAt: { gte: startDate, lte: endDate }, status: { not: 'CANCELLED' } },
}),
// New users
prisma.user.count({
where: { createdAt: { gte: startDate, lte: endDate } },
}),
]);
return {
revenue: Number(revenue._sum.total) || 0,
orders,
avgOrderValue: orders > 0 ? Number(revenue._sum.total) / orders : 0,
newUsers: users,
};
}
4.2 Time Series Metrics
// Aggregate by time granularity
export async function getRevenueTrend(
startDate: Date,
endDate: Date,
granularity: 'day' | 'week' | 'month'
) {
const format = {
day: '%Y-%m-%d',
week: '%Y-%u',
month: '%Y-%m',
}[granularity];
return prisma.$queryRaw`
SELECT
DATE_FORMAT(created_at, ${format}) as period,
SUM(total) as revenue,
COUNT(*) as orders
FROM orders
WHERE created_at BETWEEN ${startDate} AND ${endDate}
AND status != 'CANCELLED'
GROUP BY period
ORDER BY period
`;
}
4.3 Grouped Metrics
// Category distribution
export async function getCategoryDistribution(startDate: Date, endDate: Date) {
return prisma.$queryRaw`
SELECT
c.name as category,
SUM(oi.quantity * oi.price) as revenue,
SUM(oi.quantity) as quantity
FROM order_items oi
JOIN products p ON oi.product_id = p.id
JOIN categories c ON p.category_id = c.id
JOIN orders o ON oi.order_id = o.id
WHERE o.created_at BETWEEN ${startDate} AND ${endDate}
AND o.status != 'CANCELLED'
GROUP BY c.id, c.name
ORDER BY revenue DESC
`;
}
Before writing complex queries → Must read data-layer.md#data-aggregation-queries
Phase 5: Chart Planning
5.1 Visualization Type Selection
| Data Type | Recommended Component | Reason |
|---|---|---|
| Time trends | LineChart / AreaChart | Show change over time |
| Distribution | PieChart | Intuitive proportion display |
| Rankings | BarChart (horizontal) | Easy comparison and reading |
| Multi-metric comparison | ComposedChart | Combine bar and line charts |
| Status distribution | PieChart / BarChart | Show counts per status |
| Detailed records | DataTable | Sortable, filterable, paginated list |
| Transaction logs | DataTable | Search, filter, export capabilities |
| Item listings | DataTable | With actions (view, edit, delete) |
5.2 Layout Type Selection
Ask user about their dashboard purpose to recommend a layout:
What is the primary purpose of this dashboard?
1. Executive Overview - High-level KPIs for quick decision-making
2. Operations Monitoring - Real-time data and alerts
3. Deep Analysis - Multi-dimensional filtering and exploration
4. Period Comparison - YoY/MoM comparison and benchmarking
| Layout Type | Best For | Key Features |
|---|---|---|
| Executive Dashboard | C-level, managers | KPI cards + main trend + distribution |
| Operational Dashboard | Operations team | Real-time status + live table + alerts |
| Analytical Dashboard | Analysts | Sidebar filters + drill-down + detailed table |
| Comparison Dashboard | Strategy, planning | Period selector + dual charts + change analysis |
Before implementing layout → Must read dashboard-patterns.md#common-bi-layout-patterns
5.3 Layout Structure
Default Executive Dashboard layout:
┌─────────────────────────────────────────────────────────┐
│ Filter Bar: [Date Range] [Category] [Status] [Apply] │
├─────────┬─────────┬─────────┬───────────────────────────┤
│ KPI 1 │ KPI 2 │ KPI 3 │ KPI 4 │
│ Revenue │ Orders │ AOV │ New Users │
├─────────────────────────────┬───────────────────────────┤
│ │ │
│ Revenue Trend (Line) │ Category Dist (Pie) │
│ lg:col-span-2 │ │
│ │ │
├─────────────────────────────┴───────────────────────────┤
│ │
│ Top 10 Products (Bar Chart) │
│ │
├─────────────────────────────────────────────────────────┤
│ Order Details (DataTable) │
└─────────────────────────────────────────────────────────┘
Phase 6: Page Implementation
6.1 Directory Structure
app/dashboard/
├── page.tsx # Main page
├── loading.tsx # Loading skeleton
└── components/
├── kpi-cards.tsx # KPI cards
├── revenue-chart.tsx # Revenue trend chart
├── category-pie.tsx # Category pie chart
├── top-products.tsx # Product ranking
├── data-table.tsx # Reusable DataTable component
├── columns.tsx # Table column definitions
├── filters.tsx # Filters
└── export-button.tsx # Export button
lib/
├── prisma.ts # Prisma client
└── metrics.ts # Metric calculation functions
app/api/dashboard/
├── route.ts # Combined data API
├── kpi/route.ts # KPI API
├── revenue/route.ts # Revenue trend API
└── categories/route.ts # Category data API
6.2 Implementation Order
- Prisma client →
lib/prisma.ts - Metric functions →
lib/metrics.ts - API routes →
app/api/dashboard/ - KPI cards → Simplest, verify data flow first
- Chart components → Implement one by one
- Filters → Add interactivity
- Export functionality → Complete last
6.3 Component Implementation
Chart components must use "use client" and ResponsiveContainer:
"use client";
import { ResponsiveContainer, LineChart, Line, XAxis, YAxis, Tooltip } from "recharts";
export function RevenueChart({ data }: { data: { period: string; revenue: number }[] }) {
return (
<ResponsiveContainer width="100%" height={300}>
<LineChart data={data}>
<XAxis dataKey="period" />
<YAxis />
<Tooltip />
<Line type="monotone" dataKey="revenue" stroke="hsl(var(--primary))" />
</LineChart>
</ResponsiveContainer>
);
}
Before creating chart components → Must read recharts-guide.md for the corresponding chart type
Before creating DataTable components → Must read table-patterns.md
Before implementing page layout → Must read dashboard-patterns.md
Before implementing export functionality → Must read export-patterns.md
Quick Reference
Prisma Commands
npx prisma db pull # Pull schema from database
npx prisma generate # Generate Prisma Client
npx prisma studio # Open database management UI
Chart Color Scheme
const CHART_COLORS = [
"hsl(221, 83%, 53%)", // blue
"hsl(142, 71%, 45%)", // green
"hsl(38, 92%, 50%)", // amber
"hsl(0, 84%, 60%)", // red
"hsl(262, 83%, 58%)", // purple
];
Responsive Breakpoints
// KPI row
<div className="grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-4 gap-4">
// Main chart area
<div className="grid grid-cols-1 lg:grid-cols-3 gap-4">
<div className="lg:col-span-2">{/* Large chart */}</div>
<div>{/* Small chart */}</div>
</div>
Reference Document Usage Rules
⚠️ Do not read all documents upfront. Only load on-demand when entering the corresponding phase.
Required Reading Triggers
| Trigger Timing | Must Read | Section |
|---|---|---|
| Entering Phase 4 (before writing Prisma queries) | data-layer.md | #data-aggregation-queries |
| Entering Phase 5 (when selecting chart types) | recharts-guide.md | Corresponding chart type section |
| Entering Phase 6 (before implementing page layout) | dashboard-patterns.md | #responsive-grid-layout #kpi-card-component |
| When user needs DataTable | table-patterns.md | Full document |
| When user needs export functionality | export-patterns.md | Full document |
Document Index
- data-layer.md - Prisma queries, Schema analysis, API design
- recharts-guide.md - Chart code examples by type
- table-patterns.md - DataTable with sorting, filtering, pagination
- dashboard-patterns.md - Page layouts, KPI cards, filters
- export-patterns.md - CSV export, image export