Case Study
Analytics Pipeline & Reporting System
A modular analytics pipeline that converts raw operational data into trustworthy metrics, dashboards, and reporting tables — built for clarity, accuracy, and long-term scalability.
Project type
Data analytics pipeline
Input
Raw operational data
Output
KPIs & dashboards
Focus
Accuracy & structure
The problem
Analytics often break down when raw data is inconsistent, duplicated, or poorly structured. Dashboards become slow, metrics don’t match, and stakeholders lose trust in the numbers. A clean pipeline was needed to ensure every metric has a clear origin.
The solution
This analytics pipeline separates ingestion, transformation, and reporting. Raw data is validated and normalized first, then transformed into analytics-ready tables that power dashboards and reports with confidence.
Key features
- Structured ingestion of raw datasets
- Validation and normalization steps
- Clear metric definitions (single source of truth)
- Pre-aggregated reporting tables for performance
- Supports dashboards, exports, and scheduled reports
- Designed for extension as data volume grows
Architecture
The pipeline is modular: each stage is isolated so changes in one area don’t silently affect reported metrics elsewhere.
Pipeline stages
- Ingest (raw sources)
- Validate (schema & rules)
- Transform (joins & calculations)
- Aggregate (daily / monthly)
- Serve (dashboards & exports)
Reporting tables
- metrics_daily
- metrics_monthly
- category_breakdown
- trend_analysis
Outcome
A reliable analytics foundation where numbers can be trusted. Dashboards load faster, metrics stay consistent, and future reporting requirements can be added without restructuring the entire system.
Video
Pipeline walkthrough (optional)
Optional walkthrough showing data flow from raw input to dashboard output.
Gallery
Analytics views
Data flow, transformations, and dashboard-ready outputs.
Need analytics you can trust?
If your dashboards feel slow or unreliable, I can design an analytics pipeline that keeps numbers consistent and scalable.