TV Series Database

The Project

We built an enterprise platform that centralizes, enriches, and synchronizes television and film data from over 9 external sources. The system serves as the central control hub for maintaining a high-quality content database — with automated data reconciliation, quality scoring, and real-time monitoring of streaming availability.

Challenge

TV metadata is scattered across numerous sources — from international film databases and public broadcasting media libraries to streaming platforms. Data quality varies significantly, formats are inconsistent, and availability changes constantly. Editorial maintenance was a manual, error-prone process. We needed a system that automatically aggregates data, intelligently reconciles it, and reduces the workload for our editorial team.

Core Features

• Multi-Source Integration: Automated connection to 9+ external data sources — international film databases, public broadcasting media libraries, streaming platforms, and knowledge bases are synchronized on a regular basis.
• Intelligent Matching Engine: Fuzzy matching algorithms reconcile series, seasons, and episodes across sources — with configurable thresholds and manual review for uncertain matches.
• Streaming Monitoring: Real-time monitoring of availability on German streaming platforms and media libraries with automatic URL validation and expiration detection.
• Data Quality Scoring: Automatic assessment of completeness and consistency at the episode, season, and series level — prioritizing editorial review needs.
• Release Tracking: Hourly monitoring of release portals with automatic parsing and assignment to existing records.
• Editorial Dashboard: Comprehensive admin panel with ticket system, activity logging, task monitoring, and automatic escalation for recurring errors.
• Automated Enrichment: Cast and crew data, posters, ratings, and popularity metrics are automatically imported and updated from external sources.
• Wikipedia Import: Specialized import of German episode lists with special handling for established series formats.

Technical Highlights

• Extensive data architecture with over 70 data models and complex relationships spanning multiple domains
• 82 specialized commands for automated data processing — from import and enrichment to quality calculation
• Fault-tolerant API integration with health monitoring at minute intervals, automatic deactivation after outages, and ticket creation for recurring errors
• Around-the-clock task pipeline — time-scheduled synchronization distributed throughout the day with prioritized execution order
• Scalable queue architecture for compute-intensive API operations in the background
• Seamless audit logging of all editorial changes with user statistics and session tracking

Result

The platform has fundamentally changed editorial data maintenance: what previously required manual research across dozens of sources now runs largely automated. The matching engine reduces duplicates, quality scoring efficiently prioritizes review work, and streaming monitoring consistently delivers up-to-date availability data. The team can focus on content work instead of data procurement.