Refreshing the page is the action that you need to take before the extension is available for use in projects after uploading it to Oracle Analytics Cloud. An extension is a custom plug-in that adds new functionality or enhances existing functionality in Oracle Analytics Cloud. You can download extensions from Oracle Analytics Library, which is a repository of extensions created by Oracle and the community. You can also create your own extensions using the Extension SDK, which is a software development kit that provides tools and resources for developing extensions. To upload an extension to Oracle Analytics Cloud, you need to go to the Console page and select Plug-ins from the menu. Then you need to click on Upload and browse for the extension file (.zip) that you want to upload. After uploading the extension, you need to refresh the page to see the extension in the list of available plug-ins. You can then enable or disable the extension as needed. The other actions, such as enabling the plug-in from the Plug-in menu, restarting the OAC instance, or taking no additional action, are not required or correct before the extension is available for use in projects. Reference:Oracle Help Center,Oracle Help Center,Oracle Help Center

To edit and create a new semantic model in Oracle Analytics Cloud Enterprise Edition, you need to have the BI Data Model Author role. This role allows you to access and use the Data Modeler tool, where you can create and modify semantic models that define the logical structure and relationships of your data sources. You can also use the Data Modeler to create calculations, hierarchies, variables, security filters, and other features for your semantic models. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]

There are two possible ways to design the data flow and load data for these two separate data sets in data storage:

Create two separate data flows for the Country and Sales data sets. Then call one data flow from another using a Call Data Flow step. This will allow you to execute one data flow after another in a single run.

Create data flows for the Country and Sales data sets. Then create a sequence that defines the order of execution of these data flows using a Sequence step. This will allow you to run multiple data flows sequentially or in parallel. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]

After creating a data flow, you need to save the output data to a destination. You have two options to save data in Data Flow:

Data Set Storage: This option allows you to save the output data as a data set in Oracle Analytics Cloud. You can choose the name, description, and format of the data set. You can also specify whether to overwrite or append the existing data set.

Database Connection: This option allows you to save the output data to an external database that you have connected to Oracle Analytics Cloud. You can choose the connection, schema, table name, and mode of the database destination. Reference: [Oracle Help Center], [Oracle Help Center]

Semantic model created in the OA Admin tool and hierarchy created in a proper snowflake multi-table data set are two configurations that are appropriate for designing a solution to analyze retail sales with a product hierarchy in Oracle Analytics Cloud. A semantic model is a logical representation of your data that defines the relationships, calculations, hierarchies, and security rules for your data. You can create and manage semantic models using the OA Admin tool, which is a web-based interface that allows you to administer Oracle Analytics Cloud instances and services. A hierarchy is a structure that organizes your data into different levels of detail based on parent-child relationships. You can create hierarchies for your dimensions to enable drill-down analysis on your data. A snowflake multi-table data set is a type of data set that consists of multiple tables that are related to each other by foreign keys. You can create a snowflake multi-table data set using Data Preparation or Data Flow features in Oracle Analytics Cloud. You can use this type of data set to model complex dimensions that have multiple attributes stored in different tables, such as a product hierarchy with multiple levels. Reference:Oracle Help Center, [Oracle Help Center], [Oracle Help Center]