Warner Music Group: Data And the Future of the Music Business

The media industry has changed quite a bit as we all know over the last 20 years

We've gone from a physical world to a digital streaming world. 

So, we use the Snowflake Data Cloud to provide the best experience primarily for our artists. For them to understand their fans, their fan base, and consumer trends, and also helps to inform us of where we're going to invest in new artists and new content types. 

My name is Ralph Musen. I’m the global CIO of Warner Music Group.

My name is Moin Haque. I’m the SVP of Architecture and Engineering of Global Technology at the Warner Music Group.

Every time a song is played anywhere in the world on any platform, we get a record that's sent back. Currently, that's about 4.5 billion plays a day for Warner. 

And where Snowflake has really been powerful for us is it allows us to capture all of those signals and then make them accessible and available. Whereas historically, internally, a lot of our teams would have to go discover and find this data in various silos and systems.

Our artists use snowflake data cloud  on a daily basis to understand how their songs are resonating with the public and understand their fan base and what their fan base would like to see. So they can create more great content for them.

I believe the future of the media industry is more collaboration when it comes to sharing and utilizing data. I believe snowflake can greatly enable this future by providing a single source by which all media companies can upload, transact and share their data amongst themselves. 

Where Snowflake as a platform, the data exchange and the clean room are really key enablers of this future is it allows us to work with more and more varied partners in sharing our signals, in exchanging data, as well as discovering opportunities together on how to monetize it, how to identify our consumers better and how to ultimately serve them with experiences MUSIC that make the experience even more enriching.

AI and ML is becoming increasingly a tool set available to our analysts. 

In many cases, whether it's forecasting, building a propensity model or some kind of behavioral segmentation or scoring, Snowflake becomes the go-to source for them to curate these signals and then TO build models upon.

From a consumer perspective,  our goal is to really be able to drive the ability to distribute and target that content to consumers where they are, to enrich their experience beyond just listening. But to really be part of their holistic day-to-day lives.

From a performance and scalability perspective, Snowflake has been an outstanding platform for us. First and foremost, from a predictability aspect. We rarely run into concerns that if we're going to have a spike of consumption or we're going to have to shift to a different model at which we're bringing data in or pushing data out, we've been very confident in Snowflake's ability to scale up to that demand. 

Also, in partnership with each of the respective cloud partners, Snowflake really helps connect a lot of the other services that are present. So for example, today, within Amazon Web Services, our advanced analysts are heavily leveraging solutions such as SageMaker Studio.

Whereas in Google Cloud Platform, we may see extensive use of their machine learning services, having Snowflake present there, really helps drive a lot of the data ingress and egress, and makes the entire experience a lot more seamless for us.

The old world has us or the current world has us, basically manually having to get all these data sets, mix them together and make sense of them. I think it could be done in one shared communal location and the snowflake data cloud makes the most sense for that.