Thursday, April 23, 2026

Power BI Visuals — When to use with real examples

 

Power BI Visuals — When to use with real examples

1) Bar / Column – Compare categories (ranking)

✅ Use when: comparing items (Region/Product/Team)
Example: Revenue by Region, Top 10 Products by Sales
Best practice: Use bar when category names are long.


2) Line – Trend over time

✅ Use when: daily/weekly/monthly trends
Example: Tickets created per day, Monthly revenue for last 24 months
Best practice: Add moving average for noisy data.


3) Area – Trend + magnitude emphasis

✅ Use when: you want to emphasize volume over time
Example: Website traffic trend (highlight growth)


4) Combo (Line + Column) – Volume + rate together

✅ Use when: one metric is amount, another is %
Example: Sales (columns) + Margin% (line)


5) Stacked Bar/Column – Composition + total

✅ Use when: you need total + category contribution
Example: Monthly revenue split by channel (Online/Store)


6) 100% Stacked – Share only (percentage composition)

✅ Use when: share matters more than totals
Example: Incident types % share per month


7) Treemap – Part-to-whole with many categories

✅ Use when: many categories; quick proportion scan
Example: IT spend by vendor/service type
⚠️ Not best for exact comparisons.


8) Pie/Donut – Part-to-whole with very few categories

✅ Use when: 2–5 categories only
Example: Payment method share (UPI/Card/COD/Wallet)
⚠️ Avoid for many slices.


9) Waterfall – Explaining variance (bridge)

✅ Use when: “why did it change?”
Example: Profit change from last month: Price + Volume + Cost + FX


10) Scatter/Bubble – Relationship + outliers

✅ Use when: correlation and anomalies
Example: Discount% vs Units Sold (bubble size = revenue)


11) Funnel – Stage drop-off

✅ Use when: sequential pipeline with drop-offs
Example: Leads → Qualified → Proposal → Won
⚠️ Avoid if your process isn’t sequential.


12) KPI / Card – Single metric status

✅ Use when: headline metrics and executive summary
Example: Total Sales, SLA %, MTTR
Best practice: Pair with trend or target.


13) Gauge – Progress to target (use sparingly)

✅ Use when: one goal metric, executive glance
Example: SLA 92% vs target 95%
✅ Better alternative (often): Bullet chart (custom visual)


14) Table – Row-level detail

✅ Use when: transaction-level audit view
Example: Invoice list, Ticket list, Backup job list


15) Matrix – Hierarchy + drill

✅ Use when: grouped summary with drill-down
Example: P&L (GL → Sub-GL → Account), Region → Country → City


16) Decomposition Tree – Root cause exploration

✅ Use when: “why is this high/low?” with guided drill
Example: Defects → Plant → Line → Shift → Defect type


17) Key Influencers – Driver analysis

✅ Use when: “what influences churn/late delivery?”
Example: Drivers of churn: tenure, plan type, complaints, region


18) Map / Filled Map – Geographic patterns

✅ Use when: geography adds insight
Example: Tickets by city/state, sales by state
⚠️ Avoid if location is just a label.

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About the Author : Anurag Pandey | Database cloud Architect | Oracle | SQL Server | PostgreSQL | AI and Data Platform Enthusiast

Anurag Pandey is a Database Architect with expertise in Oracle, PostgreSQL, SQL Server, Linux, and enterprise database platforms and specializes in database architecture, performance tuning, high availability, disaster recovery, cloud modernization, and operational excellence. With extensive experience in enterprise-scale environments, Anurag is passionate about leveraging AI, automation, and modern data platforms to improve reliability, scalability, and business outcomes. He actively contributes to technical communities through knowledge sharing, architecture guidance, and thought leadership in database and data engineering domains.

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