Analytics & BI

Snowflake, Matillion, and Tableau Implementation for Global Music Distribution Platform

The Situation

The world's leading digital music aggregator, distributing music from independent artists to platforms including Spotify and Apple Music, had outgrown its MySQL reporting environment. Explosive growth in streaming data had created bottlenecks across every part of their data pipeline. Key challenges included:

  • Nightly data refreshes taking nine hours to complete
  • Query load times degrading significantly as data volumes grew
  • Data polymorphism challenges causing tables to run inefficiently
  • A data analytics team spending the majority of their time on troubleshooting and maintenance rather than generating insights for the business

What We Did

Delivered a proof of concept to validate the Snowflake, Matillion, and Tableau stack against real data before a full commitment was made

  • Stood up Snowflake as a scalable cloud data platform, using zero-copy cloning to support Dev, Prod, and Deployment environments without duplicating storage
  • Implemented Matillion's CDC feature for incremental data refreshes, reducing query load on the source system
  • Resolved data polymorphism modeling challenges, creating a workflow to get data into a clean, analytics-ready format
  • Built two baseline Tableau dashboards covering content copyright review and marketing new client inflow analytics
  • Proceeded to full production implementation following successful proof of concept

Results

  • Nightly data refresh time reduced from nine hours to 30 minutes
  • Data analytics team freed from pipeline troubleshooting to focus on generating insights for other business units
  • Proof of concept passed leadership review, leading to a full production rollout of the Snowflake, Matillion, and Tableau stack
  • Data analytics team gained clarity on the skills and roles needed to grow their internal capability

What This Unlocks

For media companies or platforms managing high-volume, rapidly growing data from multiple external sources, this engagement demonstrates how a Snowflake proof of concept can de-risk a full platform investment while delivering immediate performance gains. The data polymorphism modeling approach and incremental refresh patterns are directly reusable for any organization ingesting complex, high-volume streaming or transactional data.

Team

Led by a data lead and data architect handling architecture and Matillion implementation, supported by an analytics solutions lead and analytics consultant delivering Tableau dashboard design and development.

Back to Snowflake Use Cases
SnowflakeMatillionTableaudata architecturemediamusicstreamingproof of conceptincremental refreshUSA

Need help with Snowflake
planning, implementation or optimization?

InterWorks uses cookies to allow us to better understand how the site is used. By continuing to use this site, you consent to this policy. Review Policy OK

×

Interworks GmbH
Ratinger Straße 9
40213 Düsseldorf
Germany
Geschäftsführer: Mel Stephenson

Kontaktaufnahme: markus@interworks.eu
Telefon: +49 (0)211 5408 5301

Amtsgericht Düsseldorf HRB 79752
UstldNr: DE 313 353 072

×

Love our blog? You should see our emails. Sign up for our newsletter!