Practice Free Salesforce Certified Tableau Consultant Exam Online Questions

Question #1

A client requests a published Tableau data source that is connected to SQL Server. The client needs to leverage the multiple tables option to create an extract. The extract will include partial data from the SQL Server data source.

Which action will reduce the amount of data in the extract?

A . Use an extract filter.
B . Aggregate the extract to the visible dimensions.
C . Define the filters by using custom SQL.
D . Set up the extract as an incremental refresh.

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Correct Answer: A
A

Explanation

Using an extract filter is an effective way to reduce the amount of data in a Tableau extract. Extract filters allow you to specify a subset of the data to include, which can significantly decrease the size of the extract by excluding unnecessary data. This is particularly useful when you only need partial data from a larger SQL Server data source.

References: The recommendation to use extract filters to reduce data size is supported by Tableau’s best practices for optimizing extracts. These practices suggest keeping the extract’s data set short through filtering1.Additionally, discussions in the Tableau Community confirm that hiding fields and using extract filters before extracting data can help reduce the extract size2.

When dealing with large datasets in SQL Server and needing to create a manageable extract in Tableau, using an extract filter is the most direct and effective method to limit the data included:

– Extract Filter: This involves setting filters that apply directly when the data is extracted from the source. This means that only the data meeting the specified criteria will be extracted and loaded into Tableau, significantly reducing the size of the extract.

– To apply an extract filter, in the Data Source page in Tableau, drag the fields you want to filter by to the Filters shelf. Then, configure the desired filter criteria. When you create the extract, choose the option to "Add Filters to Extract" and select the configured filters. This ensures that only the data that meets these conditions is extracted from the SQL Server.

This approach not only minimizes the data volume but also speeds up performance in Tableau because it processes a smaller subset of the full dataset.

References: This procedure is described in detail in Tableau’s help documentation on managing extracts and optimizing performance by using extract filters, which is recommended for scenarios involving large datasets or when specific subsets of data are required for analysis.

Question #2

A client has many published data sources in Tableau Server. The data sources use the same databases and tables. The client notices different departments give different answers to the same business questions, and the departments cannot trust the data. The client wants to know what causes data sources to return different data.

Which tool should the client use to identify this issue?

A . Tableau Prep Conductor
B . Ask Data
C . Tableau Catalog
D . Tableau Resource Monitoring Tool

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Question #3

A new Tableau user created a simple dashboard on Tableau Server using supply chain data. Now, the user wants to know if they created the dashboard in

accordance with specific performance best practices.

Which approach should the consultant recommend for the client to make this determination?

A . Use inbuilt dashboards in Tableau Server to troubleshoot the performance.
B . Use Performance Recording on Tableau Server.
C . Use Performance Recording in Tableau Desktop.
D . Run Workbook Optimizer.

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Question #4

A client creates a report and publishes it to Tableau Server where each department has its own user group set on the server. The client wants to limit visibility of the report to the sales and marketing groups in the most efficient manner.

Which approach should the consultant recommend?

A . Grant access to the report on the Tableau Server only to the members of sales and marketing user groups.
B . Prepare a row-level security (RLS) entitlement table to define limitations of the access and use it to build user filters in the report’s data source.
C . Add user filters from Tableau Server to each worksheet and select only sales and marketing user groups.
D . Use user groups defined on Tableau Server to build user filters in the report’s data source.

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Question #5

A client has several long-term shipping contracts with different vendors that set rates based on shipping volume and speed. The client requests a dashboard that allows them to model shipping costs for the next week based on the selected shipping vendor. Speed for the end user is critical.

Which dashboard building strategy will deliver the desired result?

A . Recommend that the client model for only profitability for the next 24 hours instead of a full week.
B . Calculate the potential shipping cost for each order with each vendor, display the aggregate costs in a large table, and use quick filters to limit the options visible to the user.
C . Aggregate the orders then use a calculated field that refers to a user-selected parameter to calculate the shipping costs.
D . Use a calculated field that refers to a user-selected parameter to calculate shipping costs for each order and then display the aggregate
values.

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Question #6

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?

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.

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Correct Answer: B
B

Explanation

Moving calculations to the data layer and materializing them in the extract can significantly improve the performance of reports in Tableau. The calculation ZN([Sales])*(1 – ZN([Discount]))is a basic calculation that can be easily computed in advance and stored in the extract, speeding up future queries. This type of calculation is less complex than table calculations or LOD expressions, which are better suited for dynamic analysis and may not benefit as much from materialization12.

References: The answer is based on the best practices for creating efficient calculations in Tableau, as described in Tableau’s official documentation, which suggests using basic and aggregate calculations to improve performance1.Additionally, the process of materializing calculations in extracts is detailed in Tableau’s resources2.

Given that all files share the same schema and have a common element in their file names, the wildcard union is an optimal approach to combine these files before performing any transformations.

This strategy offers the following advantages:

Efficient Data Combination: Wildcard union allows multiple files with a common naming scheme to be combined into a single dataset in Tableau, streamlining the data preparation process.

Uniform Schema Handling: Since all files share the same schema, wildcard union ensures that the combined dataset maintains consistency in data structure, making further data manipulation more straightforward.

Pre-Transformation Combination: Combining the files before applying transformations is generally more efficient as it reduces redundancy in transformation logic across multiple files. This means transformations are written and processed once on the unified dataset, rather than repeatedly for each individual file.

References:

Wildcard Union in Tableau: This feature simplifies the process of combining multiple similar files into a single Tableau data source, ensuring a seamless and efficient approach to data integration and preparation.

Question #7

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?

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

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Question #8

A client wants to see the average number of orders per customer per month, broken down by region. The client has created the following calculated field:

Orders per Customer: {FIXED [Customer ID]: COUNTD ([Order ID])}

The client then creates a line chart that plots AVG (Orders per Customer) over MONTH(Order Date) by Region. The numbers shown by this chart are far higher

than the customer expects.

The client asks a consultant to rewrite the calculation so the result meets their expectation.

Which calculation should the consultant use?

A . {INCLUDE [Customer ID]: COUNTD ([Order ID])}
B . {FIXED [Customer ID], [Region]: COUNTD ([Order ID])}
C . {EXCLUDE [Customer ID]: COUNTD ([Order ID])}
D . {FIXED [Customer ID], [Region], [Order Date]: COUNTD ([Order ID])}

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Question #9

A consultant plans a Tableau deployment for a client that uses Salesforce. The client wants users to

automatically see Tableau views of regional sales filtered by customer as soon as the users sign into Salesforce.

Which approach should the consultant use to deliver the final visualization?

A . Embed views into Salesforce.
B . Create a list of URLs that the users can click in Salesforce.
C . Publish to Tableau Mobile for viewing.
D . Create subscriptions for each view to deliver reports by email.

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Question #10

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?

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.

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