Which of the following are benefits of using Data Extracts in Tableau?

• A.Improved Performance
• B.Ability to use the data offline
• C.Working with freshest data at all times
• D.Faster to work with

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_________________ is useful when you need to change how the data source is configured on a sheet-by-sheet basis, and when you want to combine databases that don't allow relationships or joins

• A.Union
• B.Data Joining
• C.Data segregation
• D.Data Blending

Correct Answer: D

Explanation
Data blending is performed on a sheet-by-sheet basis and is established when a field from a second data source is used in the view. To create a blend in a workbook already connected to at least two data sources, bring a field from one data source to the sheet-it becomes the primary data source.
Switch to the other data source and use a field on the same sheet-it becomes a secondary data source. An orange linking icon will appear in the data pane, indicating which field(s) are being used to blend the data sources.

According to the official Tableau Documentation:

To read more about Data Blending, click on THIS link.

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We can use ______________ as a static tool to open and interact with packaged workbooks with extracted data sources that have been created in Tableau Desktop.

• A.Tableau Reader
• B.Tableau Online
• C.Tableau Server
• D.Tableau Desktop

Correct Answer: A

Explanation
The word 'static tool' gives it away.
According to the official website :

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Tableau auto-generates ____________ dimension(s) and _____________ measure(s) for us

• A.1 , 4
• B.2 , 2
• C.2 , 3
• D.1 , 2

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You can use the __________________ in Tableau to clean / organise your data.

• A.Data cleaner
• B.Data manager
• C.Data interpreter
• D.Data organiser

Correct Answer: C

When you track data in Excel spreadsheets, you create them with the human interface in mind. To make your spreadsheets easy to read, you might include things like titles, stacked headers, notes, maybe empty rows and columns to add white space, and you probably have multiple tabs of data too.
When you want to analyze this data in Tableau, these aesthetically pleasing attributes make it very difficult for Tableau to interpret your data. That's where Data Interpreter can help.

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