Agent skill

analytics-design

Design data analysis from purpose clarification to visualization. Use when analyzing data, exploring BigQuery schemas, building queries, or creating Looker Studio reports.

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Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/analytics-design-yusuke-suzuki-dotfiles

SKILL.md

Analytics Design

Rules: Follow document-writing and text-formatting-ja for Japanese documents.

Workflow

Use references/analytics-design-template.md to document every analysis.

  1. Clarify Purpose: What do you want to know? Why is this analysis needed? Who will use it? One-time or ongoing monitoring?

  2. Discover Data: Explore available datasets and understand schema.

    • Ask user for project/dataset context and business background
    • Use /bq-query skill for BigQuery schema exploration
    • db/schema.rb for Rails projects
    • API docs or sample data for external services
    • Document schema and table relationships in the report
  3. Build Query: Use /bq-query skill to design and execute queries.

    • Requirements and schema from Steps 1-2 provide context
    • Interpret results and document findings
  4. Create Dashboard (if ongoing monitoring needed):

    • Use references/looker-studio-template.md to design
    • Define decisions: What actions will users take based on this dashboard?
    • Check existing resources: Similar dashboards or queries already exist?
    • Align time granularity with usage frequency (daily/weekly/monthly)
    • Design data sources, pages, and charts

Looker Studio Best Practices

Reference Documentation

  • Data types: Field data types (Number, Text, Date & Time, Currency, Percent, etc.)
  • Types of charts: Chart types (Time series, Combo chart, Table, etc.)
  • Parameters: Data source parameters

Settings Documentation

  • Verify setting names against actual Looker Studio UI before documenting
  • Use exact terminology from the UI

Data Source Design

  • One data source per analytical purpose
  • Pre-aggregate in SQL for performance
  • Include bucket fields for distribution analysis
  • Include sort-order fields for proper chart ordering
  • Descriptive data source names

Report Structure

  • Separate pages by time granularity (daily/monthly)
  • Group related metrics per page
  • Consistent filter scopes within pages

Chart Type Selection

Purpose Chart Type
KPI current value Scorecard
Time series trend Time series chart
Category breakdown over time Stacked area / Stacked bar
Category comparison Bar chart
Composition Pie chart
Detailed data Table
Distribution (percentile) Time series (multiple metrics)

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