Now that you know what metadata is, it's time to explore why data analysts use it. You already know that data needs to be identified and described before it can help you solve a problem or make an effective business decision. Putting data into context is probably the most valuable thing that metadata does, but there are still many more benefits of using metadata. Here's one. Metadata creates a single source of truth by keeping things consistent and uniform. We data analysts love consistency. We always aim for this kind of uniformity in our data and our databases. After all, data that's uniform can be organized, classified, stored, accessed, and used effectively. Plus, when a database is consistent, it's so much easier to discover relationships between the data inside it and the data elsewhere. Metadata also makes data more reliable by making sure it's accurate, precise, relevant, and timely. This also makes it easier for data analysts to identify the root causes of any problems that might pop up. The bottom line is, when the data we work with is high quality, it makes things easier and improves our results. One of the ways data analysts make sure their data is consistent and reliable is by using something called a metadata repository. A metadata repository is a database specifically created to store metadata. Metadata repositories can be stored in a physical location, or they can be virtual, like data that exists in the cloud. These repositories describe where metadata came from, keep it in an accessible form so it can be used quickly and easily, and keep it in a common structure for everyone who may need to use it. Metadata repositories make it easier and faster to bring together multiple sources for data analysis. They do this by describing the state and location of the metadata, the structure of the tables inside, and how data flows through the repository. They even keep track of who accesses the metadata and when. Here's a real-world example. As a health care analyst at Google, I use second and third party data. As you learned, second party data is data that's collected by a group directly from its audience and then sold. Third party data comes from outside sources, which are not the original collectors of that data. They get it from websites or programs that pull the data from the various platforms where it was originally generated. It's a bit complex, but the main thing to remember is that third party data doesn't come from inside your own business. If my team needs to work with data that wasn't created at Google, that means we sometimes don't know very much about its quality and credibility, but we need to be certain that our data can be trusted and was collected responsibly. After all, if the data is unreliable, our results can be unreliable too. That's why understanding the metadata of the external database is so important. It lets us confirm that the data is clean, accurate, relevant, and timely. This is particularly important if the data comes from another organization. One other important step when working with external data is confirming that we're allowed to use it. We'll often reach out to the owner to make sure we can access or purchase it. To sum up, metadata repositories are useful for all these reasons. Plus, they help ensure that my team is pulling the right content for the particular project and using it appropriately. We can confirm this because the metadata clearly describes how and when the data was collected, how it's organized, and much more. Soon you'll learn even more about using metadata in data analytics, and if you're finding metadata particularly fascinating, you'll discover some really exciting career choices that focus on metadata. Stay tuned.