In an era of online streaming and the increase in data volume, Copyright Management Organizations (CMOs) are struggling to keep up. A new appproach is needed to deal with the ever increase in data volumes, in order to efficiently pay song writers and artists.
Spanish Point Technologies’ Matching Engine is a SaaS solution that is helping CMOs cope with large data volumes. It helps identify songs of performance records consumed on digital platforms, so CMOs can achieve better results in the distribution of royalties when compared to existing systems.
To cope with the increased number of transactions per month, as well as the revenue per transaction, many CMOs have had to move from SQL Server to a Software as a Service solutions (SaaS) in order to optimize the recent explosion in data volumes associated with streaming services such as Spotify or YouTube.
The Matching Engine solution is a more modern and adaptable system, less expensive to maintain, and highly scalable. It is a SaaS solution that runs in the cloud helping CMOs, publishers and similar organizations to handle the exponential growth of data volumes in the music industry. The high-performance engine of the Matching Engine supports organisations addressing metadata errors and ensure music royalties are tracked with accuracy.
The company favours an agile approach to software development, ensuring customers like CMOs are involved and informed every step of the way; keeping the customer experience front of mind in order to create bespoke solutions that are both user-friendly and innovative.
Spanish Point began developing the Matching Engine solution in February, 2012, choosing only Microsoft Azure based components such as Azure Search, Azure Databricks and Spark to configure a sophisticated cloud based platform that helps CMOs deal with their metadata issues while adapting to the new era of online streaming.
Using cloud-based technologies the Matching Engine is able to use automated scaling to process the data in a fraction of the time that it would have taken previously.
The Matching Engine which also uses machine learning and advanced algorithms to accelerate data processing, has lowered transaction processing times from 12 hours to 5 minutes.
The constant innovation and improvements in the Matching Engine are design, methodologies and software development tasks, but Spanish Point’s ability to bring together different teams of engineers to identify potential innovations through an agile approach and technical intensity is what defines Spanish Point’s mindset and has helped to develop the Matching Engine. The Matching Engine ensures that song writers and artists receive the payments they deserve by helping CMOs to identify the large number of performance records consumed in digital platforms and matching them to existing CMO repertoires.