Can it help with business intelligence and reporting?

Absolutely. It generates complex SQL views that aggregate raw data into business-ready metrics like Monthly Recurring Revenue (MRR), churn rates, and active user counts.

Which data sources are supported by this skill?

It is designed to handle Stripe subscription data, Vercel deployment logs, Expo mobile analytics, and various external API or CSV sources.

How does it handle data quality issues?

The skill includes a dedicated validation pipeline that checks for required fields, type mismatches, and data age, automatically flagging or quarantining records that fail validation.

Is the sync process safe to run multiple times?

Yes, it uses idempotent upsert logic (on-conflict resolution) to ensure that repeated syncs do not create duplicate records or corrupt existing data.

Data Consolidation Specialist

Name: Data Consolidation Specialist
Author: coreymaypray

bycoreymaypray

0•

데이터베이스 관리

Automates complex ETL pipelines and aggregates multi-source metrics into centralized Supabase databases for real-time reporting.

The Data Consolidation skill transforms fragmented data from Stripe, Vercel, Expo, and external APIs into a unified, queryable source of truth within Supabase. It automates the entire lifecycle of data management, from cleaning and validation to the creation of high-performance SQL views and consolidated dashboards. This skill is ideal for teams needing reliable, cross-platform metrics like MRR, churn rates, and user activity without the manual overhead of traditional data engineering.

주요 기능

01High-performance SQL view generation for consolidated dashboards

02Robust data validation and cleaning with quarantine logging

03Automated ETL pipelines between Stripe, Vercel, and Supabase

04Idempotent upsert logic ensuring data integrity and freshness

050 GitHub stars

06Automated derived metric calculations for MRR, ARR, and Churn

사용 사례

01Unifying revenue data from Stripe with application usage from Supabase into a single dashboard

02Automating daily syncs of Vercel deployment logs into a central database for performance monitoring

03Migrating and cleaning legacy CSV data into structured tables with automated error reporting

주요 기능

01High-performance SQL view generation for consolidated dashboards

02Robust data validation and cleaning with quarantine logging

03Automated ETL pipelines between Stripe, Vercel, and Supabase

04Idempotent upsert logic ensuring data integrity and freshness

050 GitHub stars

06Automated derived metric calculations for MRR, ARR, and Churn

사용 사례

01Unifying revenue data from Stripe with application usage from Supabase into a single dashboard

02Automating daily syncs of Vercel deployment logs into a central database for performance monitoring

03Migrating and cleaning legacy CSV data into structured tables with automated error reporting