Thursday, April 23, 2026

Practical “which Power BI visual to use when” guide - Part 1

 

1) First ask: What question are you answering? (Fast decision guide)

✅ A) Compare values across categories

➡️ Use Bar/Column chart
Examples:

  • “Which product sold the most?”
  • “Which region has highest revenue?”

✅ B) Trend over time (change, seasonality)

➡️ Use Line / Area / Combo chart
Examples:

  • “Monthly revenue trend last 24 months”
  • “Tickets trend day-by-day”

✅ C) Part-to-whole (composition)

➡️ Use Treemap / 100% stacked bar (avoid pie unless very few categories)
Examples:

  • “Revenue contribution by product category”
  • “Spend by cost head”

✅ D) Relationship / correlation

➡️ Use Scatter/Bubble chart
Examples:

  • “Does discount % increase sales?”
  • “Does delivery time impact customer rating?”

✅ E) Distribution (how values spread)

➡️ Use Histogram (custom) / Box plot (custom) / Column with bins
Examples:

  • “Order value distribution”
  • “Response time distribution (SLA)”

✅ F) Progress vs Target / KPI tracking

➡️ Use KPI / Card / Gauge (limited use) / Bullet chart (best if available)
Examples:

  • “Sales vs Target”
  • “SLA compliance %”

✅ G) Flow / stages (pipeline)

➡️ Use Funnel (only when it truly narrows stage-by-stage)
Examples:

  • “Leads → Qualified → Proposal → Won”

✅ H) Contribution to change

➡️ Use Waterfall chart
Examples:

  • “Why profit changed from last month to this month?”

✅ I) Ranking changes over time

➡️ Use Ribbon chart
Examples:

  • “Top 5 products rank by month”

✅ J) Detailed reporting / audit view

➡️ Use Table / Matrix
Examples:

  • “Invoice-level detail”
  • “P&L with hierarchy (GL → Sub-GL → Account)”

✅ K) Geography-based insights

➡️ Use Map / Filled map (only when geography matters)
Examples:

  • “Sales by state/district”
  • “Service tickets by city”

2) Visuals explained with when to use + real case

2.1 Bar / Column (Most used)

Best for: Comparing categories; ranking.
When to choose:

  • More than 5–7 categories? Prefer bar (horizontal) for readability.
  • Need Top N? Use bar + Top N filter.

Real case: Retail Sales Dashboard

  • Visual: Bar chart
  • Question: “Top 10 SKUs by Revenue”
  • Slice by: Region, Channel, Month
    ✅ Clear ranking, easy to compare.

Avoid: Too many categories without Top N (becomes clutter).


2.2 Line chart (Trend over time)

Best for: Time series (daily/weekly/monthly).
Real case: Support Ops

  • Visual: Line
  • Metric: Tickets created vs resolved per day
  • Insight: Identify backlog growth or improvements.

Best practice: Add moving average or trend line for noisy data.


2.3 Combo chart (Line + Column)

Best for: Two metrics with different behavior (e.g., volume + rate).
Real case: Sales Performance

  • Columns: Monthly Sales
  • Line: Gross Margin %
    This helps answer: “Sales increased but did margin drop?”

2.4 Stacked / 100% Stacked

Best for: Composition across categories (and change over time).

  • Stacked bar: shows absolute + composition
  • 100% stacked: shows share % only

Real case: HR Analytics

  • 100% stacked by Month: Attrition split (Voluntary / Involuntary)
    Shows “attrition mix changing?” irrespective of total.

2.5 Treemap (Part-to-whole with many categories)

Best for: Many categories where you want quick proportional view.
Real case: IT Spend

  • Treemap: Cost by Vendor → Service Type
    Instantly shows biggest spend blocks.

Avoid: Precise comparison (humans struggle comparing rectangle areas).


2.6 Pie/Donut (Use carefully)

Use only if:

  • Max 2–5 categories
  • One category clearly dominates
    Real case: Payment Method Share (UPI, Card, COD, Wallet) if only 4.

Avoid: 10 slices = unreadable. Use bar instead.


2.7 Waterfall (Explaining variance)

Best for: “What changed and why?”
Real case: Finance

  • Profit change from Q1 to Q2 explained by: Price effect, Volume effect, Cost increase, FX impact.
    Perfect for bridge analysis.

2.8 Scatter / Bubble (Correlation + outliers)

Best for: Relationship between 2 measures, detect clusters/outliers.
Real case: E-commerce pricing

  • X: Discount %
  • Y: Units sold
  • Bubble size: Revenue
    Helps answer: “Which products respond to discount and which don’t?”

2.9 Funnel (Stage drop-off)

Best for: Sequential stages with drop-offs.
Real case: Sales CRM pipeline

  • Leads → Qualified → Proposal → Closed
    Shows conversion and leakage.

Avoid: If your process isn’t sequential (then use bar).


2.10 KPI / Card / Gauge (Single number)

Card: “Total Sales”, “Total Tickets”, “MTTR”
KPI visual: shows value + target + trend
Gauge: okay for exec view, but limited comparison (bullet is better).

Real case: SLA Monitoring

  • KPI: SLA compliance % vs target 95% with trend over time
  • Cards: Open tickets, Avg resolution time

2.11 Table vs Matrix (Detail & Hierarchies)

Table: flat row-level detail (invoice list, ticket list)
Matrix: hierarchical (Region → Country → City, or GL hierarchy)

Real case: P&L report

  • Matrix: Revenue, COGS, Opex with drill-down
  • Conditional formatting for variance % (green/red)

2.12 Decomposition Tree (Root cause analysis)

Best for: “Why is this high/low?” with drill-based explanation.
Real case: Manufacturing defects

  • Start: Total Defects
  • Drill: Plant → Line → Shift → Operator → Defect type
    Great for operations and RCA.

2.13 Key Influencers (Driver analysis)

Best for: “What factors influence churn / late delivery / defect?”
Real case: Customer churn

  • Target: Churn = Yes/No
  • Explain by: Tenure, plan type, complaints, region
    Gives data-driven drivers quickly.

2.14 Maps (Geography)

Use if location matters and you have geo fields (state/city/lat-long).
Real case: Service Coverage

  • Filled map by state: ticket density
  • Drill to city hotspots

Avoid: If geography is just a label and doesn’t add insight.


3) Common mistakes (and what to do instead)

❌ Using Pie for everything

✅ Use bar/treemap for many categories.

❌ Too many visuals on one page

✅ Use 3–6 strong visuals, then drill-through for details.

❌ No context (no target, no benchmark)

✅ Add target lines, previous period, variance %, tooltips.

❌ Same scale issues in combo charts

✅ Use combo only when it makes sense; ensure right axis is clear.


4) Recommended “real dashboard layouts” (templates)

Template A: Sales Performance (Exec)

  1. Cards: Revenue, Profit, Margin%, YoY%
  2. Line: Revenue trend (Monthly)
  3. Bar: Top 10 Products
  4. Map: Revenue by state (optional)
  5. Waterfall: Profit variance vs last quarter
  6. Matrix: Region → Channel breakdown with drill

Template B: Ops / Support

  1. KPI: SLA%, MTTR
  2. Line: Created vs Resolved tickets
  3. Bar: Tickets by Category
  4. Scatter: Resolution time vs CSAT (outliers)
  5. Table: Ticket-level drill-through

5) Quick cheat-sheet (one-liners)

  • Compare categories: Bar/Column
  • Trend: Line
  • Trend + Target: Line + constant line / KPI
  • Part-to-whole (many): Treemap / stacked
  • Explain change: Waterfall
  • Correlation/outliers: Scatter
  • Pipeline stages: Funnel
  • Geography: Map
  • Root cause drill: Decomposition tree
  • Drivers: Key influencers
  • Details/audit: Table/Matrix

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