Challenge
Pattern research becomes difficult when business logic is buried in scripts and cannot be reviewed, versioned, or reused by other platform modules.
Analytics Engine
Pattern Recognition Analytics Engine
A configurable pattern recognition layer for market and business datasets, built for experimentation, review, and dashboard consumption.
Project narrative
From workflow problem to engineered analytics system.
Each project explains the client-style challenge, software solution, modules, architecture, implementation choices, and compliance-aware boundaries.
Solution
The engine separates data ingestion, rule configuration, feature calculation, result storage, review workflows, and visualization so new patterns can be added without rewriting the platform.
Core modules
Rule configuration
Feature calculation pipeline
Pattern result storage
Review dashboard
Historical comparison
Audit metadata
Architecture highlights
Python analytics services
Reusable calculation modules
PostgreSQL storage for derived results
Background job execution with task queues
AI-assisted classification notes for review workflows
Stack
Technology used
PythonDjangoPandasNumPyPostgreSQLCelery
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