Low Fidelity Mockups

Why this matters

As a Data Visualization Engineer, you turn questions into clear dashboards and reports. Low-fidelity mockups let you validate layout, flow, and chart choices fast—before you spend time on data prep and pixel-polish. Use them to align with stakeholders, surface edge cases, and reduce rework.

• Real tasks: sketch KPI dashboards; choose chart types; place filters; plan drilldowns; map annotations and legends.
• Outcome: a shared picture of what will be built and why, ready for quick feedback.

Concept explained simply

A low-fidelity mockup is a quick, simplified drawing of your dashboard or report. Think boxes, labels, arrows, and notes—no colors, exact fonts, or real data. It focuses on what matters: information hierarchy, layout, interactions, and decisions.

Mental model

Boxes and labels, not pixels. Imagine packing a suitcase: big items first (primary KPIs), then medium (key charts), then small (filters, legends, annotations). If it doesn’t fit on paper, it won’t fit on screen.

Core elements of a good low-fi mockup

• Layout grid: define zones (e.g., header, KPI strip, main charts, details).
• Hierarchy cues: larger boxes and bold labels for what matters most.
• Chart placeholders: simple shapes labeled “Bar,” “Line,” “Table,” etc.
• Interactions: annotate filters, drilldowns, hover tooltips, and states.
• Context: titles, timeframes, units, and data refresh cadence.
• Constraints: note target device (desktop/mobile), expected width, and scroll behavior.

Simple workflow

1. Clarify the question: what decision should this view support?
2. List the metrics and dimensions that matter.
3. Draft layout zones with a grid (e.g., 12 columns).
4. Place chart placeholders and add labels.
5. Mark interactions and states (filtering, drill, comparison).
6. Review with stakeholders, capture feedback, iterate quickly.

Worked examples

Example 1: Executive revenue dashboard (desktop)

• Header: title + date range selector.
• KPI strip: Revenue, YoY Growth, Avg Order Value (large text, trend sparkline boxes).
• Main: left “Revenue by Region (Map/Bar),” right “Revenue Trend (Line).”
• Bottom: “Top Products (Bar)” and “Customer Segments (Stacked Bar).”
• Notes: hover tooltips with YoY deltas; click region filters downstream charts.

Example 2: Incident monitoring view (wide screen)

• Top alert banner with thresholds and last refresh time.
• 3-column mid-section: “Incidents by Severity (Stacked Bar),” “Time to Resolve (Box),” “Open vs Closed (Area).”
• Bottom table with search and severity filter chips.

Example 3: Mobile sales pulse (phone)

• Single-column stack: date picker, KPI cards (Revenue, Orders, Conversion), mini line for 7-day trend, and a compact bar for Top Channels.
• Thumb-friendly filters at bottom; minimal scrolling.

Hands-on exercises

These mirror the graded exercises below. Use paper, a whiteboard, or basic shapes in your favorite design tool.

Exercise 1: Executive revenue dashboard

Sketch a low-fi for an executive dashboard that answers: “How is revenue trending, and where should we focus?”

• Must include: three KPI cards (Revenue, YoY Growth, AOV), a line trend, a regional breakdown, a top products chart, and a global date filter.
• Annotate: which elements filter others, tooltip content, and any drilldowns.

Exercise 2: Investigative funnel view

Sketch a low-fi for a conversion funnel that answers: “Where do we lose users most, and what changed week over week?”

• Must include: funnel chart, WoW comparison (small multiples or dual bars), dimension filter chips (device, country), and a detailed table of drop-off reasons.
• Annotate: how selecting a funnel step filters the table and which comparison windows are supported.

Exercise checklist

• Clear title and timeframe shown.
• Primary KPIs are visually prioritized.
• Each chart has a purpose label.
• Interactions (filters, drills, tooltips) are annotated.
• Units and aggregation levels are noted.
• Device/viewport assumptions are stated.

Common mistakes and how to self-check

• Too much fidelity: colors, exact fonts, and real data at this stage slow feedback. Self-check: can someone understand it in black-and-white?
• Unlabeled charts: placeholders without purpose. Self-check: every box has a descriptive label like “Monthly Revenue (Line).”
• No interaction notes: stakeholders assume different behaviors. Self-check: for any filter or click, write what changes.
• Cramming: everything looks equally important. Self-check: vary box sizes and positions to show hierarchy.
• Ignoring constraints: desktop plan used on mobile. Self-check: write target width/viewport and scroll plan.

Practical projects

• Portfolio piece: create low-fi mockups for two contrasting use cases: an executive KPI dashboard and an analyst exploration view. Show iterations with notes.
• Usability test: show your low-fi to two different stakeholders and record three changes you made based on their feedback.
• Mobile adaptation: convert a desktop low-fi into a mobile-first version while preserving the decision flow.

Who this is for

• Data Visualization Engineers who need quick stakeholder alignment.
• Analytics Engineers and BI Developers shaping dashboards and reports.
• Analysts preparing specs for implementation.

Prerequisites

• Basic understanding of common chart types and when to use them.
• Clarity on the business question and core metrics.
• Awareness of your BI tool’s layout constraints (roughly).

Learning path

1. Low-fi mockups (you are here): layout, hierarchy, interactions.
2. Component patterns: KPI cards, legends, filters, tooltips.
3. High-fidelity prototypes: color, typography, accessibility.
4. Build and validate: implement in your BI tool and test.

Next steps

• Complete the exercises and compare with sample solutions.
• Run a 15-minute feedback session using your low-fi.
• Take the quick test to confirm understanding. Note: the test is available to everyone; only logged-in users get saved progress.

Mini challenge

Pick any report you maintain. In 10 minutes, redraw it as a low-fi focusing on the key decision it supports. Remove one chart that doesn’t serve that decision. Annotate one new interaction that would reduce clicks.

Quick Test

Ready to check your understanding? Take the short test below. It’s available to everyone; only logged-in users get saved progress.