Revlon’s comprehensive cloud has matured, and the benefits from aggressively embracing the cloud have evolved into positive consequences for their data architecture.
When you think of Revlon, we’re global and we have a huge application portfolio. As we put everything on our cloud and are using our cloud, we realized that all of our data sits in one place now.
So when you think of big-data management, we’ve been able to solve the problem by classifying all the unstructured data in Revlon and we did that efficiently. We still joke that it’s like chewing glass. You’ve got to go through this huge process.
But, we have the ability to look at all of our data, a couple of petabytes, in the same place. Because the cloud let us look at it all, we can bring up all of Revlon in our disaster recovery (DR) test environments and have our developers work with it at no cost. We have disconnected that cost and effort.
Once we realized we had this opportunity to start working on our big data, the other unintended consequences was our master data model. On top of our big data, we were able to able to efficiently and effectively build a global master data model.