Dashboard Design Templates

20+ production-ready dashboard layouts for Tableau, Looker, and Power BI. Each template includes wireframe specifications, metric placement guidelines, color palettes, and implementation code. Designed for executive, operational, and self-service analytics use cases.

Key Features

• 20+ Dashboard Layouts — executive summary, operational, departmental, self-service explorer
• Multi-Platform Support — implementation guides for Tableau, Looker, and Power BI
• Layout Specifications — wireframes with grid systems and spacing rules
• Color Palette System — accessible, brand-adaptable palettes (sequential, diverging, categorical)
• Chart Selection Guide — decision tree for choosing the right visualization
• Mobile-Responsive Patterns — layouts that work on tablet and phone
• Interactivity Patterns — filter, drill-down, and cross-highlight implementation
• Performance Guidelines — query optimization tips for sub-5-second load times

Quick Start

1. Browse templates/ to find a layout matching your use case
2. Review the wireframe spec in docs/wireframes/
3. Copy the implementation code for your BI platform
4. Customize metrics, colors, and filters for your data

Power BI: Executive KPI Card

Revenue Current Period =
VAR _CurrentPeriod = [Total Revenue]
VAR _PreviousPeriod =
    CALCULATE(
        [Total Revenue],
        DATEADD('Calendar'[Date], -1, MONTH)
    )
RETURN
    _CurrentPeriod

Revenue MoM Change =
VAR _Current = [Revenue Current Period]
VAR _Previous =
    CALCULATE([Total Revenue], DATEADD('Calendar'[Date], -1, MONTH))
RETURN
    DIVIDE(_Current - _Previous, _Previous, 0)

Usage Examples

Tableau: Dynamic Period Comparison

// Tableau calculated field
IF [Date Selector] = "MTD" THEN
    IF [Order Date] >= DATE(YEAR(TODAY()), MONTH(TODAY()), 1)
       AND [Order Date] <= TODAY()
    THEN "Current"
    ELSEIF [Order Date] >=
           DATEADD('month', -1, DATE(YEAR(TODAY()), MONTH(TODAY()), 1))
           AND [Order Date] <= DATEADD('month', -1, TODAY())
    THEN "Previous"
    END
END

Looker: Self-Service Explorer View

view: dashboard_explorer {
  derived_table: {
    sql:
      SELECT
        d.date_key,
        d.fiscal_quarter,
        p.product_category,
        r.region_name,
        f.revenue,
        f.units_sold,
        f.discount_amount
      FROM fact_sales f
      JOIN dim_date d ON f.date_key = d.date_key
      JOIN dim_product p ON f.product_key = p.product_key
      JOIN dim_region r ON f.region_key = r.region_key
    ;;
  }

  dimension: product_category {
    type: string
    sql: ${TABLE}.product_category ;;
  }

  measure: total_revenue {
    type: sum
    sql: ${TABLE}.revenue ;;
    value_format_name: usd_0
  }

  measure: avg_discount_pct {
    type: average
    sql: ${TABLE}.discount_amount / NULLIF(${TABLE}.revenue, 0) ;;
    value_format_name: percent_1
  }
}

Color Palette Specification

palettes:
  sequential_blue:
    - "#E8F0FE"   # Lightest — low values
    - "#A8C7FA"
    - "#4285F4"
    - "#1A56DB"
    - "#0B3D91"   # Darkest — high values
  diverging_red_blue:
    - "#D93025"   # Below target
    - "#F28B82"
    - "#F5F5F5"   # Neutral
    - "#A8C7FA"
    - "#1A56DB"   # Above target
  status:
    on_track: "#34A853"
    at_risk: "#FBBC04"
    off_track: "#EA4335"

Dashboard Templates Index

#	Template	Best For	Key Metrics
1	Executive Summary	C-suite	Revenue, churn, NPS, pipeline
2	Sales Performance	Sales leadership	Pipeline, win rate, quota
3	Marketing Funnel	Demand gen	Traffic, MQLs, SQLs, CAC
4	Product Usage	Product team	DAU/MAU, adoption, retention
5	Customer Health	CS team	Health score, NPS, tickets
6	Financial Overview	Finance	P&L, cash flow, burn rate
7	Engineering Velocity	Eng leadership	Cycle time, throughput
8	HR People Analytics	People ops	Headcount, attrition, DEI

Best Practices

1. Start with the question, not the chart — every element must answer a specific business question
2. Above the fold matters — place 3-5 most important KPIs at the top left
3. Limit to 7±2 visual elements — cognitive overload kills comprehension
4. Use consistent date ranges — all charts should share the same time context
5. Design for the 5-second test — viewers should grasp the main message immediately
6. Progressive disclosure — summary on top, details via drill-down or tabs

Troubleshooting

Issue	Cause	Fix
Dashboard loads >10s	Too many queries or large extracts	Pre-aggregate data; use extracts over live connections
Colors hard to distinguish	Too many categories	Limit to 5 categories; use provided palettes
Users ignore the dashboard	Not answering their questions	Interview 3 stakeholders before designing
Mobile layout broken	Desktop-first design	Use grid templates from templates/responsive/

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