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ZeiZel
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analytics

Optimize data analytics workflows by turning raw data into product insights.

2|Updated Oct 1, 2024
Search Tags:#analytics#dashboard#sql#etl#data-modeling#cohorts#ab-testing
One-click install
npx skills add https://github.com/ZeiZel/dotfiles --skill analytics-zeizel
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: analytics
Source: https://github.com/ZeiZel/dotfiles/tree/main/.claude/skills/analytics
Command: npx skills add https://github.com/ZeiZel/dotfiles --skill analytics-zeizel

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Data-driven decision making hinges on clean, reliable analytics pipelines and actionable metrics.

Core Features & Use Cases

  • SQL optimization and data modeling for scalable analytics
  • ETL/ELT pipeline design and dashboarding for BI
  • A/B testing design and interpretation for product experiments
  • Metrics framework design and governance to align teams

Quick Start

Create a starter metrics plan and a basic dashboard blueprint for your product.

Frequently Asked Questions about analytics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build a metrics framework for product analytics?▼

A product analytics metrics framework aligns teams by defining standardized measurements for event tracking and experimentation. This Skill designs governance plans to turn raw data into consistent, actionable insights for decision-making.

What's the best way to optimize SQL queries for scalable data modeling?▼

Optimizing SQL for scalable data modeling involves restructuring queries and schemas to handle large volumes efficiently. This Skill provides best-practice approaches to streamline your analytics workflows and improve dashboard performance.

Do I need SQL proficiency to design ETL pipelines and dashboards?▼

Yes, SQL proficiency is required to design ETL pipelines and build BI dashboards effectively. This Skill relies on SQL knowledge to model data, optimize queries, and turn raw inputs into visualized product insights.

How does A/B testing interpretation work for product experiments?▼

A/B testing interpretation analyzes experiment results to determine statistical significance and product impact. This Skill guides you through designing tests and evaluating outcomes to validate product changes and drive smarter decisions.

Can I use this Skill for cohort and retention analysis on raw data?▼

Yes, you can perform cohort and retention analysis by applying structured data modeling to your raw data. This Skill enables product and marketing teams to generate actionable insights from user behavior cohorts.

When do I need ETL pipeline design for my analytics workflow?▼

You need ETL pipeline design when raw data must be transformed and centralized for reliable BI dashboarding. This Skill helps structure your ETL/ELT processes to ensure clean data feeds into your analytics metrics framework.

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