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You have been tasked with building an analysis that requires data from two subject areas. How do you accomplish this?
To build an analysis that requires data from two subject areas, you can create an analysis and add a second subject area for a union. A union is an operation that combines two or more data sets with similar columns into one data set. You can use the Add Subject Area option in the Criteria tab of an analysis to add another subject area and select Union as the operation type. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]
Which two steps do you perform to create a Relative Time filter?
To create a relative time filter, you need to perform two steps:
Select Relative Time as the filter type: A relative time filter allows you to filter your data based on a relative time period, such as last week, next month, or current year. You can select Relative Time as the filter type from the drop-down menu of the filter bar.
Select Relative Time as the filter type and set the Relative To property: The Relative To property allows you to specify the reference point for your relative time period. For example, if you want to filter your data for the last quarter relative to today, you can set the Relative To property to Today. You can set the Relative To property from the filter dialog box after selecting Relative Time as the filter type. Reference: [Oracle Help Center], [Oracle Help Center]
You are a developer designing a solution to analyze retail sales. A key requirement for the solution is a product hierarchy with multiple levels that supports drill-down in an Oracle Analytics Cloud (OAC) workbook.
Which two configurations are appropriate for your solution?
Using Narrate insight, you can take a snapshot of any moments of any information that you see in a visualization and keep track of any moments of sudden realization while you work with the data.
You can then share these with other users. Which statement is true about sharing with Insights?
Insights is always shared in form of story so everybody will see the same information and insights is shared as a story and everybody will see their information based on permissions are two true statements about sharing with insights in Oracle Analytics Cloud. Insights are messages that appear on your canvas to inform or alert your audience about something important or relevant to your story, such as a key insight, a recommendation, or a call to action. You can create insights using the Insight icon on the toolbar and customize them by changing the text, color, position, and duration of the message. You can also enable or disable the Use Snapshot Data option for each insight in the properties panel. When you share your insights with other users, you share them as part of your story, which is a feature that allows you to create and present a narrative based on your data using various elements, such as visualizations, text boxes, images, videos, and more. You can share your story with other users by exporting it as a file (.png, .pdf, or .dva) or by sending it via email or chat. When you share your insights as part of your story, everybody will see the same information that you see in your insights, regardless of whether you use live data or snapshot data for your insights. However, everybody will also see their information based on their permissions for accessing the data sets or projects that are associated with your story. The other statements, such as it is not possible to share insights with other users and by default all users cannot share insights, are not true about sharing with insights in Oracle Analytics Cloud. You can share insights with other users as part of your story using various methods, such as exporting, emailing, or chatting. You can also control who can share insights by changing the permissions of your story in the catalog. Reference: [Oracle Help Center], [Oracle Help Center], [Oracle Help Center]
Which two statements are true about data wrangling?
Data wrangling is a process of transforming and enriching data to make it more suitable for analysis or visualization. Some statements that are true about data wrangling are:
In data wrangling, transformations available are dependent on the data type. For example, you can apply different transformations to numeric, text, date, or location data types.
It is used to curate data sets that can be used for complex visualizations. For example, you can use data wrangling to create calculated columns, merge or split columns, group or aggregate values, filter or sort rows, or join or union data sets. Reference: [Oracle Analytics Cloud - Data Visualization User's Guide], [Oracle Analytics Cloud - Data Visualization User's Guide]
