Esports: Real Time Sponsorship Data Pipeline

Monetizing Unstructured Video Streams

We transformed raw, high-volume video streams into structured, actionable business intelligence. Our real time sponsorship data pipeline established the robust infrastructure needed for accurate ROI calculation.

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Esports Brand Monitoring: Data Pipeline & Analytics

Project Overview

This project addressed a critical business need: converting massive volumes of unstructured, real-time video data into accurate, auditable sponsorship metrics. An esports client required a system to precisely calculate sponsor ROI by tracking logo appearances across live social media streams. Our Data Division's objective was to design and deploy the complex infrastructure and data processing engine—the real-time data pipeline—required to reliably ingest, process, and store this data for downstream analysis.

The Data Challenge: Ingesting Big Data From Camera Feed

The core problem was one of big data ingestion from video streams combined with demanding latency requirements.

Unstructured Data Processing Complexity

The primary data source was continuous video from live streams, creating a massive ingestion challenge where data needed to be processed before analysis could begin.

Scale and Speed

The client demanded real time sponsorship monitoring insights, requiring a pipeline capable of processing high-volume data streams without lag.

The AI Integration Hurdle

The raw video stream needed preparation before being fed into the AI model for logo recognition, requiring robust data engineering for AI-powered logo detection.

The Data Solution: Real Time Brand Tracking

We engineered a resilient, cloud-based architecture that functions as a high-performance video analytics data platform. This solution centered on building a dedicated real time sponsorship data pipeline to ensure every second of brand exposure was accurately captured and quantified.

Key goals included:

High-Volume Ingestion: Developed a scalable queuing mechanism capable of big data ingestion from live video streams, securely pulling raw video frames and associated metadata.
Data Preparation Engine: Engineered an upstream service specifically for unstructured data processing, segmenting and preparing the video stream into optimized batches for consumption by the computer vision model.
Analytics Layer: Integrated the AI model for logo recognition as a dedicated data transformation stage, converting visual information into structured data points.
Schema for ROI: Designed a structured data warehouse schema optimized for sponsorship ROI data engineering, storing actionable insights (e.g., logo exposure duration, viewer reach) for easy querying.
Advanced Analytics Enablement: The entire infrastructure was built to support sophisticated queries for deep learning sponsorship analytics computer vision solutions, ensuring high data fidelity.

The Implementation Phases

Our approach focused on building the reliable data foundation first, then integrating the advanced analytics layer.

I: Infrastructure Provisioning

Set up the cloud environment and configured the streaming services (queues, APIs) for high-speed data flow.

II: Data Pipeline Development (ETL)

Built the end-to-end flow to handle the raw video streams and perform initial metadata extraction.

III: Analytics & Schema Design

Designed the database architecture, creating the final schema for the reporting warehouse and optimizing the data model for ROI calculation.

IV: Real-Time Deployment & Monitoring

Deployed the full solution, integrating the AI model for logo recognition output, and implementing data quality checks.

The Outcomes: Before Data Solutions Vs. After Data Solution

The implementation of the real-time sponsorship data pipeline provided the client with a competitive advantage rooted in data reliability.

Metric / Area

BEFORE Data Solution

AFTER Data Solution

Speed & Latency

ROI calculation required hours or days of manual post-event analysis.

Insights are extracted in near real-time during the live stream, enabling instant real-time sponsorship monitoring.

Data Accuracy

Subjective, approximate data (e.g., "logo was visible for most of the match").

100% quantifiable metrics delivered by the video analytics data platform, based on precise frame-level data.

Data Source/Scale

Reliance on inconsistent third-party view data and manual review.

Big data ingestion from video feeds ensures comprehensive, automated collection from multiple sources.

Business Reporting

No dedicated data structure for reporting on brand exposure.

Successful in building a data platform for brand monitoring ROI, providing instant, auditable reports.

Turn Raw Streams into Structured Intelligence

Video and streaming data are untapped sources of massive value. We specialize in processing unstructured video data for ROI and setting up the resilient data infrastructure you need. Whether you require a cloud data solution for real-time sponsorship tracking or complex sensor data processing, our team can deliver.

Our Team

Built by Engineers. Led by Thinkers. Driven by Results.

At Folio3 Data, we’ve built a team that doesn’t just understand data. They know how to make it meaningful. From our leadership to delivery teams, every person here brings a sharp mind, a hands-on approach, and a real commitment to solving complex problems.

We're a team that becomes an extension of yours - thinking with you, building beside you, and staying until it works.