Centralised Data Warehouse for VeVe’s Digital Collectibles Platform

Vodworks designed and delivered a scalable data platform for VeVe. With automated pipelines, built-in data quality controls and near-real-time availability, VeVe gained a clearer view of sales, customer activity and business

Consolidated nine data sources into a single source of truth
Delivered a scalable data warehouse with near-real-time data pipelines
Improved data quality, reporting and visibility across sales and customer transactions

About The Client

VeVe is a digital collectibles and entertainment platform created to bring traditional collecting into the digital world. The platform enables collectors to discover, buy, sell, collect and display officially licensed digital collectibles, comics and artworks.

Veve’s partnerships include globally recognised brands such as Disney, Marvel, Star Wars, DC and Lamborghini. With more than eight million digital collectibles and NFTs sold, over 200 collectible brands and customers in more than 150 countries, VeVe operates a global ecosystem connecting intellectual-property owners with a large community of collectors.

Market: Global
Industry: Digital Collectibles & Entertainment
Services Provided: Data architecture, data engineering, cloud infrastructure, systems integration, data quality, reporting and DevOps

The Scope

VeVe’s business data was distributed across nine source systems and stored in structured and semi-structured formats. Without a centralised data warehouse, teams lacked one consistent view of the information needed for reporting, analytics and day-to-day decisions.

Data fragmentation made it difficult to trace the complete lifecycle of buy and sell transactions. Investigating customer queries required significant manual effort, while inconsistent values, duplicate records and missing data made reconciliation across systems time-consuming. It also limited the business’s ability to monitor sales performance and identify emerging issues quickly.

Vodworks was engaged to design and implement a secure, scalable and cost-effective data platform that could:

Integrate data from the existing structured and semi-structured sources
Establish a centralised warehouse as a reliable source of truth
Standardise data and identify inconsistencies, duplicates and missing records
Make current data available for reporting with minimal latency
Support growing data volumes and the addition of future sources
Protect data integrity while keeping infrastructure and operating costs under control

How Vodworks Helped

Vodworks took end-to-end ownership of the data platform, from solution planning and architecture through implementation, testing, deployment and ongoing optimisation.

Building the data foundation from the ground up

As a greenfield project, the engagement gave the team the opportunity to design an architecture around VeVe’s specific data and scalability requirements. We implemented a central Amazon Redshift warehouse supported by Amazon S3 for scalable storage and staging.

Airbyte and custom Python pipelines ingest data from the source systems, while Dagster orchestrates extraction, transformation and loading workflows. Reusable pipeline components made it possible to bring different data formats into a unified model without requiring major changes to VeVe’s existing applications.

Making data quality part of the pipeline

Quality and reliability controls were built directly into the data workflows. Automated validation identifies inconsistent values, missing records and duplicates early, before they affect downstream reporting.

By standardising and reconciling data as it moves through the platform, the solution gives VeVe a more dependable view of sales, customer activity and transaction lifecycles. It also makes it easier for teams to investigate customer queries and trace issues back to their source.

Scaling large workloads efficiently

One of the most demanding technical challenges was managing large-scale backfills in Dagster without allowing parallel jobs to consume excessive CPU and memory in Kubernetes.

Vodworks introduced defined resource limits, tuned memory configurations and controlled the number of concurrent runs. Configurable Dagster run settings allow the team to adjust resource allocation without changing application code. This approach supports high-volume processing while maintaining stable performance and close control over infrastructure costs.

Connecting data with business operations

The platform was integrated with VeVe’s wider analytics and operational ecosystem. Metabase provides reporting and data exploration, while integrations with Redpanda, Customer.io and AWS services connect the warehouse with event streams, customer communications and operational data.

AWS IAM and Secrets Manager support secure access and credential management. CloudWatch monitoring, automated alerts and CI/CD pipelines help the team operate and evolve the platform reliably.

Tech stack

The Results

Vodworks delivered a fully operational data warehouse that gives VeVe consistent, timely and centralised data for reporting, analytics and business decision-making.

Key project achievements include:

Consolidated data from nine structured and semi-structured sources into one scalable warehouse
Reduced inconsistencies and duplicate records through automated validation and standardisation
Improved the traceability of buy and sell transactions, supporting more efficient investigation of customer queries
Enabled more reliable reporting and clearer visibility into sales, customer activity and overall business performance
Reduced manual effort across ingestion, transformation, reconciliation and monitoring workflows
Delivered data with minimal latency to support more timely operational and business decisions
Created a flexible foundation that can accommodate growing data volumes, new source systems and evolving reporting requirements