The main drivers behind Stream Governance go beyond simply managing data effectively. Data drives some of today's most important business use cases but it's often treated as a byproduct and left up to others to build ad-hoc ways of accessing it. We need to stop treating data as a byproduct and start treating it as a first-class product instead. Data as a product is the foundation of many companies that have become critical to the global economy. Now, that doesn't necessarily mean we need to sell the data outside our company, but we should be thinking about how to make better use of it inside our company. With that in mind, let's talk about what makes a product successful. Many products succeed because they offer consistency that people couldn't get otherwise. If you buy a McDonald's hamburger, you know what it will taste like, regardless of where you order it. Similarly, we make use of schemas and the Schema Registry to create a data contract that guarantees every message looks the same. This consistency builds trust in the brand and allows our data products to be successful. Sometimes a product succeeds because of how easy it is to access. This kind of ubiquity is what made Netflix a breakout success and drove other industries such as video rental into oblivion. Being able to easily find and consume content has been a major driver in the digital media economy. Applied to data streams, this means that a successful product needs to be easy to find and easy to use. This, of course, is driven by the Stream Catalog. Often, a product is more successful because of how well it integrates with the world around it. Apple has long been known for building products that work incredibly well together. This integrated approach means that Apple customers know exactly how each individual product will fit into their lifestyle. It's part of what keeps them coming back for more. If we want users to consume more than one of our data products, then we need this level of integration. Users need to understand exactly how their piece of the puzzle fits into a larger data mesh. Seeing the integration points mapped out in real time in the stream lineage, helps them understand the bigger picture. Truly successful products need to be reliable. For many years, Toyota has topped the list of reliable auto manufacturers. When someone buys a Toyota, they have confidence that it will be a strong and safe investment for years to come. In the case of data, we achieve this reliability by ensuring the data is available and secure. Security features like RBAC can help guarantee the data is accessible to those who need it, and won't be compromised. Together, the Stream Governance tools enable us to construct a data platform that can be foundational to our business. This allows teams to view data as a critical product of the system rather than an afterthought. The data-as-a-product model is a key principle that drives our digital transformation. If you would like to understand more about how data streams can be turned into data products, and how those products can be integrated into a data mesh, check out the Confluent Developer Course, Data Mesh 101. If you aren't already on Confluent Developer, head there now using the link in the video description to access the rest of this course and its hands-on exercises.