Dashboard vs Report

Technical Explanation

Dashboards and reports serve different purposes. Understanding when to use each is fundamental to effective data communication.

Dashboard vs Report Comparison

Aspect	Dashboard	Report
Purpose	Monitor status	Document details
Updates	Real-time/continuous	Periodic/snapshot
Interactivity	High (filters, drills)	Low (static)
Data depth	Summary	Detailed
Audience	Broad, recurring	Specific, one-time

When to Use a Dashboard

• Monitoring KPIs daily/continuously
• Comparing metrics across segments
• When decisions happen frequently
• When different viewers need different views

When to Use a Report

• Detailed analysis for a decision
• One-time investigation
• Regulatory/compliance documentation
• When you need to see individual records

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Code Examples

Using the CatCafe dataset:

-- DASHBOARD QUERY: Summary metrics for monitoring
-- (High-level, fast to read, updateable)
SELECT
    DATE_TRUNC('day', order_date) as date,
    COUNT(*) as orders,
    SUM(total_amount) as revenue,
    COUNT(DISTINCT customer_id) as customers
FROM orders
WHERE status = 'completed'
AND order_date >= CURRENT_DATE - INTERVAL '7 days'
GROUP BY DATE_TRUNC('day', order_date)
ORDER BY date;

-- REPORT QUERY: Detailed transaction list
-- (Detailed, for audit or one-time analysis)
SELECT
    o.id as order_id,
    o.order_date,
    c.name as customer_name,
    c.email as customer_email,
    o.total_amount,
    o.status,
    cat.name as cat_name
FROM orders o
JOIN customers c ON o.customer_id = c.id
LEFT JOIN order_items oi ON o.id = oi.order_id
LEFT JOIN cats cat ON oi.cat_id = cat.id
WHERE o.order_date >= '2024-01-01'
AND o.order_date < '2024-02-01'
ORDER BY o.order_date DESC;

-- DASHBOARD: KPI summary
SELECT
    COUNT(DISTINCT customer_id) as active_customers,
    SUM(total_amount) as total_revenue,
    AVG(total_amount) as avg_order_value,
    COUNT(*) as total_orders
FROM orders
WHERE status = 'completed'
AND order_date >= CURRENT_DATE - INTERVAL '30 days';

-- REPORT: Detailed customer list with all attributes
SELECT
    c.id,
    c.name,
    c.email,
    c.phone,
    c.city,
    c.registration_date,
    COUNT(o.id) as order_count,
    SUM(o.total_amount) as lifetime_value
FROM customers c
LEFT JOIN orders o ON c.id = o.customer_id
WHERE c.registration_date >= '2024-01-01'
GROUP BY c.id, c.name, c.email, c.phone, c.city, c.registration_date
ORDER BY lifetime_value DESC;

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The Cat Analogy

Dashboard = Cat's health tracker (you check daily):

Energy: ●●●○○ (3/5)
Steps: 4,500 / 6,000
Water: OK
Sleep: Good

Quick status check, action if red

Report = Cat's vet visit summary (detailed analysis):

Full examination results:
- Weight: 10.2 lbs (up from 9.8 lbs)
- Teeth: Mild tartar buildup
- Bloodwork: All values normal
- Recommendations: Dental cleaning in 3 months
Detailed explanation of each finding

Same cat, different purposes!

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Exercises

Exercise 1

When would you use a dashboard vs a detailed report?

Exercise 2

Convert this report into dashboard KPIs: "Here are all 1,247 transactions from Q1 with customer details, order items, and payment information."

Exercise 3

What makes a dashboard good for monitoring but bad for detailed analysis?

Exercise 4

Design both a dashboard and a report for tracking monthly revenue.

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Key Takeaways

• Dashboards: Monitor, summary, continuous, interactive
• Reports: Document, detailed, periodic, static
• Use dashboards for recurring decisions
• Use reports for one-time analysis or documentation
• Don't build dashboards when a periodic report suffices