In this module, we started with introduction to Looker, including a review of its role in the data analysis process. Then we completed a walkthrough of the Looker user interface and its key features. To wrap up this module, let's review a few key points about the Looker user interface. Explores are the central component of Looker, that allow business and data analysts to conduct self-served data exploration, analysis, and visualization. Explores are curated by Looker developers using LookML, a proprietary templating language, and are typically composed of a single dataset, such as order items, which contains information related to items that have been ordered. Explores are organized under headings such as e-commerce training, so that users can easily access related data. In the Looker user interface, you can see all the explores is that you have access to under the explore options on the left side navigation panel. Within an explore, the data are organized into views, but typically represent a single table in a database, such as a table containing information about users. Views contain dimensions which are data attributes such as the country where a user lives, and measures which are aggregates of dimensions such as count. You can use explores to combine dimensions and measures to answer questions and create visualizations of the results, such as a bar chart of the number of users per country. Once you have obtain the desired result and created a visualization in an explorer, you can save the results as a look, which is a standalone report or visualization. You can also save your results to a dashboard which can contain more than one visualization. Each visualization in the dashboard is referred to as a tile. For example, recall that the new users acquired visualization is a tile in the business pulse dashboard. Both looks and dashboards can be saved to multiple boards, which contains links to multiple looks, and explores, and can be easily shared with others. This means that when the underlying dashboards and looks are updated, the board chose the latest version. That's dashboards contain multiple visualizations, they show you various pieces of information about some overall topic or domain, similar to how a dashboard on a car shows you various aspects of your car's performance. For example, the business pulse dashboard shows the number of new users acquired, the average amount they spent per order, average amount each bends in their lifetime, number of orders and so on. Looker supports many kinds of visualizations out of the box and you'll try some of them in the hands-on labs. In Looker, looks and dashboards are all stored in folders just as files on your computer or Google Drive are stored in folders. Folders can contain any number of sub folders. Shared folders is the home or root folder of the entire Looker instance. Now that we have a basic understanding of Looker and its key features, we can dive into the core analytics concepts of Looker in the next module to start analyzing and visualizing data.