Barriers to Scaling Data-Driven Insight in Media



So on the left hand side here, you see that input column for a moment about all of the different sources, origin sources of your data, where it’s driving from. Right you’ve got all of your third party, you know, your content partners that are delivering data for you. You have all of your in-house systems, right. You kind of pull the veil back even further on those in-house systems. You know, you’ve got your authentication layer of your direct to consumer app, your payment gateway for your direct consumer at the actual application layer itself. So all that interactivity that your subscribers have with your applications. And then lastly, even quality of experience, looking at startup times, rebuff for rates, average bit rate quality, all of that kind of jumbled together. Right, can provide valuable insights into your business. So how do you get all that data, first off, into its system? Right to kind of start creating a data like. And you got to think about how do I normalize it, right? How do I find common data fields that I can have all of this data come into? Because a lot of these sources are delivering that data, different cadence, different volume, different breadth of data and, you know, different kind of portals and different ways to consume it. How do you find that kind of map KPIs around the different data fields that you want, then create kind of your modeling, write your algorithms. How do you analyze all of that? And then lastly, that integration component. Now, how are you actually executing off of all of that data that you have? Just analyze, actually do some testing and figure out if this data is accurate. So most organizations resort to analyzing less data. So hard to scale back and slow down strategic business decision making in a very fast paced industry. And so it’s really critical to have an enterprise solution that can help automate manual workflows and find previously unknown data sets that could potentially positively impact the business.