Relationships in data models will query only the tables and fields needed to create a visualization. This ensures efficiency in data retrieval and reduces unnecessary processing. Additionally, relationships are aware automatically of the native level of detail of logical tables, allowing for accurate and optimized data representation based on the inherent granularity of the data.

Examples of date values are specific instances in time that usually include a day, month, and year. January 1, 1995 is a specific date presented in a common written format, while 2020-05-01 is a specific date in ISO format. December and Wednesday represent a month and a day of the week, respectively, and are not complete date values.

The three reasons to use joins instead of relationships are: when you need to use a specific join type, when you need to use row-level security, and when you need to use a data model that supports shared dimensions. Using a specific join type allows for more control over how data from different tables is combined. Row-level security is often implemented via joins to restrict access to specific rows of data. Data models that support shared dimensions can be more effectively managed with joins.

Using an extract offers several benefits over a live connection to a data source. Calculated fields tend to perform better with extracts because Tableau can pre-process and optimize the data for quicker query performance. Extracts are stored in memory (RAM), leading to faster query performance as compared to live connections which rely on querying data over a network. Additionally, live connections can face performance issues due to network and user traffic, whereas extracts can mitigate these issues by operating locally.

To apply bold formatting to an axis in the view, right-click on the axis itself. This action will provide formatting options specific to the axis, including the ability to change the font style to bold.