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agent-data

Automate product analytics metrics and dashboards with materialized views and pg_cron refresh.

Updated Jan 29, 2026
Search Tags:#analytics#dashboards#metrics#etl#data-modeling#olap#pg_cron
One-click install
npx skills add https://github.com/fabiomilennials1234-a11y/v8milennialsb2bv2 --skill agent-data-fabiomilennials1234-a11y
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-data
Source: https://github.com/fabiomilennials1234-a11y/v8milennialsb2bv2/tree/main/.claude/skills/agent-data
Command: npx skills add https://github.com/fabiomilennials1234-a11y/v8milennialsb2bv2 --skill agent-data-fabiomilennials1234-a11y

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Data / Analytics engineer agent ensures reliable product metrics, dashboards, materialized aggregations, event tracking, and analytic schemas (OLAP) with refresh via pg_cron, enabling external BI ETL workflows and clear data exposure. It distinguishes from a DBA, which optimizes OLTP schemas and runtime queries; the Data role focuses on analytics and decision-support.

Core Features & Use Cases

  • Defines core product metrics across domains (funnel, time, origin, campaign, copilot, product, revenue) and exposes them via analytics views.
  • Builds analytic schemas (star schema with dimension and fact tables), uses materialized views with pg_cron refresh, and supports partitioned event tables for performance.
  • Tracks product events with versioned schemas and supports multi-tenant isolation using row-level security (RLS).
  • Provides dashboards for admin masters and orgs, with export options and ad-hoc querying capabilities.

Quick Start

Configure the analytics contract, map sources, and establish a materialized-view refresh cadence to begin collecting product metrics for an organization.

Frequently Asked Questions about agent-data

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

FAQPage Schema
How do I automate materialized view refresh for product analytics dashboards?▼

Automate materialized view refresh for product analytics dashboards using pg_cron. This Skill configures scheduled refreshes to ensure metrics and aggregations remain current and available for external BI ETL workflows.

What is the difference between a DBA and a data analytics engineer for metric definition?▼

A DBA focuses on optimizing OLTP schemas and runtime queries, whereas this data analytics role focuses on metric definition, decision-support, and building OLAP analytic schemas like star schemas with dimension and fact tables.

How do I track versioned product events with multi-tenant isolation using RLS?▼

Track versioned product events with multi-tenant isolation using RLS by configuring partitioned event tables. This Skill supports versioned schemas and enforces row-level security to isolate tenant data across organizations.

Can I build a star schema with dimension and fact tables for multi-tenant organizations?▼

Yes, you can build a star schema with dimension and fact tables for multi-tenant organizations. This Skill structures analytic schemas and exposes core product metrics across domains like funnel, revenue, and campaign.

Does pg_cron work with materialized views to schedule ETL workflows?▼

Yes, pg_cron works with materialized views to schedule ETL workflows. This Skill uses pg_cron to establish a refresh cadence, automating the production of materialized aggregations and enabling clear data exposure.

What are the limitations of using materialized views for partitioned event tables?▼

Materialized views require scheduled refreshes via pg_cron to stay current, meaning data is not real-time. This Skill manages partitioned event tables for performance but relies on configured refresh cadences rather than live updates.

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