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Questions # 21:

A Tableau Cloud client has requested a custom dashboard to help track which data sources are used most frequently in dashboards across their site.

Which two actions should the client use to access the necessary metadata? Choose two.

Options:

A.

Connect directly to the Site Content data source within the Admin Insights project.

B.

Query metadata through the GraphiQL engine.

C.

Access metadata through the Metadata API.

D.

Download metadata through Tableau Catalog.

Questions # 22:

A client collects information about a web browser customers use to access their website. They then visualize the breakdown of web traffic by browser version.

The data is stored in the format shown below in the related table, with a NULL BrowserID stored in the Site Visitor Table if an unknown browser version

accesses their website.

Question # 22

The client uses "Some Records Match" for the Referential Integrity setting because a match is not guaranteed. The client wants to improve the performance of

the dashboard while also getting an accurate count of site visitors.

Which modifications to the data tables and join should the consultant recommend?

Options:

A.

Continue to use NULL as the BrowserID in the Site Visitor Table and leave the Referential Integrity set to "Some Records Match."

B.

Add an "Unknown" option to the Browser Table, reference its BrowserID in the Site Visitor Table, and change the Referential Integrity to "All

Records Match."

C.

Add an "Unknown" option to the Browser Table, reference its BrowserID in the Site Visitor Table, and leave the Referential Integrity set to

"Some Records Match."

D.

Continue to use NULL as the BrowserID in the Site Visitor Table and change the Referential Integrity to "All Records Match."

Questions # 23:

A consultant creates a histogram that presents the distribution of profits across a client's customers. The labels on the bars show percent shares. The consultant

used a quick table calculation to create the labels.

Now, the client wants to limit the view to the bins that have at least a 15% share. The consultant creates a profit filter but it changes the percent labels.

Which approach should the consultant use to produce the desired result?

Options:

A.

Use a calculation with TOTAL() function instead of a quick table calculation.

B.

Add the [Profit] filter to the context.

C.

Filter with a table calculation WINDOW_AVG(MIN([Profit]), first(), last())

D.

Filter with the table calculation used to create labels.

Questions # 24:

A client builds a dashboard that presents current and long-term stock measures. Currently, the data is at a daily level. The data presents as a bar chart that

presents monthly results over current and previous years. Some measures must present as monthly averages.

What should the consultant recommend to limit the data source for optimal performance?

Options:

A.

Limit data to current and previous years and leave data at daily level to calculate the averages in the report.

B.

Limit data to current and previous years, move calculating averages to data layer, and aggregate dates to monthly level.

C.

Move calculating averages to data layer and aggregate dates to monthly level.

D.

Limit data to current and previous years as well as to the last day of each month to eliminate the need to use the averages.

Questions # 25:

A client has a large data set that contains more than 10 million rows.

A consultant wants to calculate a profitability threshold as efficiently as possible. The calculation must classify the profits by using the following specifications:

. Classify profit margins above 50% as Highly Profitable.

. Classify profit margins between 0% and 50% as Profitable.

. Classify profit margins below 0% as Unprofitable.

Which calculation meets these requirements?

Options:

A.

IF [ProfitMargin]>0.50 Then 'Highly Profitable'

ELSEIF [ProfitMargin]>=0 Then 'Profitable'

ELSE 'Unprofitable'

END

B.

IF [ProfitMargin]>=0.50 Then 'Highly Profitable'

ELSEIF [ProfitMargin]>=0 Then 'Profitable'

ELSE 'Unprofitable'

END

C.

IF [ProfitMargin]>0.50 Then 'Highly Profitable'

ELSEIF [ProfitMargin]>=0 Then 'Profitable'

ELSEIF [ProfitMargin] <0 Then 'Unprofitable'

END

D.

IF([ProfitMargin]>=0.50,'Highly Profitable', 'Profitable')

ELSE 'Unprofitable'

END

Questions # 26:

A stakeholder has multiple files saved (CSV/Tables) in a single location. A few files from the location are required for analysis. Data transformation (calculations)

is required for the files before designing the visuals. The files have the following attributes:

. All files have the same schema.

. Multiple files have something in common among their file names.

. Each file has a unique key column.

Which data transformation strategy should the consultant use to deliver the best optimized result?

Options:

A.

Use join option to combine/merge all the files together before doing the data transformation (calculations).

B.

Use wildcard Union option to combine/merge all the files together before doing the data transformation (calculations).

C.

Apply the data transformation (calculations) in each require file and do the wildcard union to combine/merge before designing the visuals.

D.

Apply the data transformation (calculations) in each require file and do the join to combine/merge before designing the visuals.

Questions # 27:

From the desktop, open the CC workbook.

Open the Manufacturers worksheet.

The Manufacturers worksheet is used to

analyze the quantity of items contributed by

each manufacturer.

You need to modify the Percent

Contribution calculated field to use a Level

of Detail (LOD) expression that calculates

the percentage contribution of each

manufacturer to the total quantity.

Enter the percentage for Newell to the

nearest hundredth of a percent into the

Newell % Contribution parameter.

From the File menu in Tableau Desktop, click

Save.

Options:

Questions # 28:

Use the following login credentials to sign in

to the virtual machine:

Username: Admin

Password:

The following information is for technical

support purposes only:

Lab Instance: 40201223

To access Tableau Help, you can open the

Help.pdf file on the desktop.

Question # 28

From the desktop, open the CC workbook.

Open the Categorical Sales worksheet.

You need to use table calculations to

compute the following:

. For each category and year, calculate

the average sales by segment.

. Create another calculation to

compute the year-over-year

percentage change of the average

sales by category calculation. Replace

the original measure with the year-

over-year percentage change in the

crosstab.

From the File menu in Tableau Desktop, click

Save.

Options:

Questions # 29:

From the desktop, open the CC workbook. Use the US Population Estimates data source.

You need to shape the data in US Population Estimates by using Tableau Desktop. The data must be formatted as shown in the following table.

Question # 29

Open the Population worksheet. Enter the total number of records contained in the data set into the Total Records parameter.

From the File menu in Tableau Desktop, click Save.

Options:

Questions # 30:

From the desktop, open the CC workbook.

Open the Incremental worksheet.

You need to add a line to the chart that

shows the cumulative percentage of sales

contributed by each product to the

incremental sales.

From the File menu in Tableau Desktop, click

Save.

Options:

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