Design data pipelines, KPIs, and reporting systems with ETL/ELT processes.
npx skills add https://github.com/HenderOrlando/booklyapp --skill data-reporting
Please help me install this Agent Skill. Skill: data-reporting Source: https://github.com/HenderOrlando/booklyapp/tree/main/.windsurf/skills/data-reporting Command: npx skills add https://github.com/HenderOrlando/booklyapp --skill data-reporting
This Skill streamlines the process of designing and implementing robust data pipelines, defining key performance indicators (KPIs), and establishing scalable reporting systems to derive actionable insights and recommendations.
Use the data-reporting skill to define the data profile and event taxonomy for a new user authentication system.
High-intent search queries and answers about installing and using this skill.
Designing a data pipeline involves defining event taxonomies, establishing data models, and structuring ETL or ELT strategies. This ensures consistent data ingestion, transformation, and loading for downstream reporting and analytics use cases.
Defining KPIs requires establishing clear metric definitions, mathematical formulas, and reporting cadences. This creates a standardized KPI catalog that tracks business metrics like MRR or churn, enabling consistent performance monitoring and actionable reporting.
Data deduplication and lineage improve reporting quality by tracking data origin and removing redundant records. This ensures accurate aggregations, maintains data integrity, and prevents skewed insights in downstream KPI dashboards and reporting systems.
Generating actionable insights involves developing rule-based systems and machine learning models for anomaly detection and predictions. This transforms raw warehouse data into proactive recommendations and automated alerts for business intelligence.
Ensure data privacy and security during ETL processes by applying data pseudonimization and enforcing strict access controls. This protects sensitive user information while maintaining data lineage and profile usability for reporting.
A defined data profile is required before setting up a reporting system to establish data models and event taxonomies. This foundational step ensures structured data ingestion, accurate KPI tracking, and reliable insight generation.
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