Now let's view the data we just loaded. For this and a number of other tasks in this course, MongoDB Compass is the best option. Compass is a GUI client for MongoDB that enables you to view databases, filter data using queries, modify data as needed and much more. To download Compass, let's visit the MongoDB Download Center. I will just Google for it here. Click the Compass tab, and make sure you select the right distribution for your operating system. I'm running on a Mac, so I will download the latest version for OSX. Once downloaded, go ahead and install compass. It should launch upon install, but in case it doesn't, just use Spotlight to launch it. Compass should launch once installed on Windows, but in case it doesn't, just click search and type compass. Once launched, you'll see a connect screen similar to this. Now, Compass is actively developed, so exactly what you see in the Compass UI might differ from what it is as I record this video. To connect to your free tier cluster, visit the cluster page for your Atlas account. Click Connect, and click Connect Your Application. Go ahead and copy the URL connection string, and then go back to Compass. You should see a model that asks you whether you want to use the connection string you just copied to connect Compass to MongoDB cluster. Go there and do this. Compass will populate nearly all the fields in the connection form. You just need to type the password for our analytics user. Remember, that is analytics-password. Now, all of the details you need to fill in this form are included in the lecture notes for this lesson. So don't worry if Compass didn't pop up the model asking you if you simply wanted to copy in what was in the clipboard. At the very bottom of the connect form, enter Analytics Free-Tier, and click Create Favorite, so that you can easily reconnect to your free-tier atlas cluster at any time. Now, I'll click Connect, and you'll see that I'm presented with three databases. The admin and local databases are created by default and are used by MongoDB for internal bookkeeping. The database we created when we loaded data set using Mongo import is called mflix. Click mflix. You then see that the mflix database contains one collection called movies_initial with 46,014 documents in it. In MongoDB, documents are like Rose in a relational database. And documents are organized together in collections. Much in the same way that Rose make up tables in a relational database. Each document in a collection is a distinct record. In the movies_initial collection, each document stores data for one movie. Now click movies_initial. In the documents view that loads, you can scroll through the documents in this collection. Note the fields and basic shape of the documents. In the coming lessons, we'll be doing some data cleaning and reshaping of the schema in order to better enable an application and analytics. For example, note that the genre field is a simple string containing a comma separated list of genres. This makes it difficult to partition documents based on the genre. We'll do something about that in a number of other fields.
