Why this matters
BI Developers are asked questions like “Are we hitting targets?” or “Where are we leaking revenue?” Your value is turning those questions into clear visuals users trust and act on. Good mapping avoids misleading charts, reduces rework, and speeds up decision-making.
- Real tasks you will face: translating stakeholder goals into KPIs, choosing charts that fit each comparison, arranging layout and interactions, and documenting the mapping so everyone agrees before build.
- Outcome: a dashboard plan that specifies visuals, measures, filters, level of detail, and interactions.
Concept explained simply
Mapping requirements to visuals means connecting a business question to the best visual form, level of detail, and interaction pattern. Each choice should help the user answer their question faster and with less ambiguity.
Mental model: GROW → SHOW
- Goal: What decision or action will this answer?
- Result: What exact insight is needed (trend, ranking, part-to-whole, relationship, distribution, status vs target)?
- Objects: Which entities and metrics are involved? What grain (e.g., monthly by region)?
- Why now: Time horizon, freshness, and cadence.
- SHOW: pick Visuals, Layout, Interactions that surface the Result quickly.
Step-by-step mapping workflow
- Clarify the question: write one sentence that includes who/what, metric, and comparison (e.g., “Monthly revenue vs target by region”).
- Identify comparison type:
- Change over time → line/area/small multiples
- Rank/Compare categories → bar charts
- Part-to-whole → stacked bars or treemap (avoid pies for many categories)
- Relationship → scatter/bubble
- Distribution/variability → histogram/box plot
- Progress vs target → bullet/variance bar/gauge (sparingly)
- Set level of detail: define the grain (daily/monthly), dimensions (region, product), and aggregations (sum, avg). Add reference lines (target, median) if needed.
- Choose the visual: pick the simplest chart that answers the question. Prefer bars/lines over exotic visuals.
- Define interactions: filters, highlight, drill, and tooltips. Use highlight to keep context; use drill when users must inspect detail.
- Layout the page: most important KPI top-left, consistent scales, aligned axes, shared filters.
- Document it: a short spec stating chart, fields, aggregations, filters, interactions, and rationale.
Worked examples
Example 1 — “Are we hitting monthly revenue targets by region?”
- Comparison type: progress vs target + trend by time.
- Visuals:
- Top: KPI card (Current Month Revenue, variance vs target, arrow).
- Main: monthly line for Revenue with target as reference line; color last point by above/below target.
- Sidebar: bar chart by Region showing variance to target (sorted).
- Interactions: slicers for time and product; hover tooltip shows exact variance.
- Rationale: line communicates trend; bars rank regions; reference line clarifies target.
Example 2 — “Which marketing channels drive high ROI without hurting volume?”
- Comparison type: relationship + size.
- Visuals:
- Scatter: x = ROI, y = Conversions, size = Spend, color = Channel group.
- Quadrant reference lines at median ROI and median Conversions.
- Interactions: highlight on hover to keep context; channel filter.
- Rationale: scatter reveals trade-offs; quadrants segment performance.
Example 3 — “Where are delivery delays concentrated?”
- Comparison type: distribution + hotspots.
- Visuals:
- Histogram: Delivery time (days).
- Heatmap: Region vs Carrier with avg delivery time color scale.
- Box plot: Delivery time by Warehouse.
- Interactions: select outlier bins on histogram to highlight rows in heatmap.
- Rationale: histogram finds skew/outliers; heatmap locates clusters; box plot shows variability by site.
Decision aids you can use
Quick chart picker
- Time trend → line or area (single metric), small multiples (many categories).
- Rank/Compare categories → horizontal bar; add variance bars for target comparison.
- Part-to-whole → stacked bar (few parts) or treemap (many small parts).
- Relationship → scatter; add trendline or quadrants if useful.
- Distribution → histogram (shape), box plot (spread/outliers).
- Progress vs target → bullet chart or bar + target reference line.
Accessibility tips
- Do not rely only on color; use labels, patterns, or markers.
- Prefer red/blue or orange/blue over red/green.
- Keep font sizes readable and ensure sufficient contrast.
Common mistakes and self-checks
- Using pie charts for many categories → switch to sorted bars.
- Mixing scales or dual axes that mislead → prefer small multiples or two aligned panels.
- Over-aggregating (hiding problems) → add distribution or box plots.
- Cluttered dashboards → remove non-essential ink; align axes and limit colors.
- Missing targets/benchmarks → add reference lines or variance bars.
Self-check checklist
- Does each visual answer a specific question?
- Is the comparison type obvious (time, rank, part-to-whole, relationship, distribution, target)?
- Is the level of detail (grain, filters) stated?
- Can a first-time user read it without explanation?
- Would a different visual reduce steps or confusion?
Exercises (hands-on)
Complete the exercise below. The Quick Test is available to everyone; only logged-in users get saved progress.
Exercise 1 — From requirement to spec
Requirement: “The VP Sales wants to see monthly subscription revenue vs target by region and product line, quickly spot underperforming segments, and drill to account level.”
- Define the comparison types.
- Choose visuals and level of detail.
- Specify interactions and layout.
- Write a short spec that a stakeholder can approve.
Hints
- Progress vs target suggests bullet/variance bars or reference lines.
- Trend over time suggests lines.
- Ranking regions suggests bars; drill suggests a detail table.
Practical projects
- Rebuild a team status page: KPIs at top, variance bars by team, trend lines, and a detail table with conditional formatting.
- Marketing performance board: scatter for ROI vs conversions, channel filters, and spend trend small multiples.
- Operations quality dashboard: histogram and box plot for defects, heatmap for plant vs line, and drill-to-order details.
Who this is for
- BI Developers and Analysts translating business asks into dashboards.
- Anyone responsible for chart selection, dashboard layout, or stakeholder reviews.
Prerequisites
- Basic data concepts: dimensions vs measures, aggregations, time grain.
- Comfort with a BI tool (e.g., chart building, filters, reference lines).
Learning path
- Before: clarify requirements and define metrics unambiguously.
- Now: map each question to visuals, interactions, and layout.
- Next: prototype, run a quick usability review, then build.
Mini challenge
Draft a one-page spec for: “Product managers need to monitor weekly active users vs target by platform and identify cohorts with churn risk.” Include: comparison types, 3 visuals, interactions, and why each choice is the simplest way to answer the question.
Quick Test
Take the Quick Test below to check your understanding. The test is available to everyone; only logged-in users get saved progress.