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NEW QUESTION # 27
SIMULATION
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.
Answer:
Explanation:
See the complete Steps below in Explanation
Explanation:
To modify the Percent Contribution calculated field to use a Level of Detail (LOD) expression and accurately calculate the percentage contribution of each manufacturer to the total quantity, follow these steps:
Open the CC Workbook and Access the Worksheet:
Double-click on the CC workbook from the desktop to open it in Tableau Desktop.
Navigate to the Manufacturers worksheet by selecting its tab at the bottom of the window.
Modify the Percent Contribution Calculated Field:
Navigate to the Data pane and find the "Percent Contribution" calculated field.
Right-click on the "Percent Contribution" field and select 'Edit'.
Modify the formula to incorporate an LOD expression that calculates the total quantity across all manufacturers and the specific quantity per manufacturer:
{FIXED [Manufacturer]: SUM([Quantity])} / {SUM([Quantity])}Quantity])}
This formula uses {FIXED [Manufacturer]: SUM([Quantity])} to compute the total quantity contributed by each manufacturer, regardless of other dimensions in the view. The total quantity {SUM([Quantity])} calculates the grand total across all manufacturers. The division calculates the percentage contribution.
Click 'OK' to save the updated calculated field.
Enter Percentage for Newell:
With the updated "Percent Contribution" field, drag it onto the view to update the chart or table.
Identify the value corresponding to 'Newell' in the updated visualization.
Round this value to the nearest hundredth of a percent as required.
Enter this value into the "Newell % Contribution" parameter. To do this, locate the parameter in the Data pane or on the dashboard, right-click it, and choose 'Edit'. Enter the calculated percentage for Newell.
Save Your Changes:
From the File menu, click 'Save' to store all the modifications you have made to the workbook.
References:
Tableau Help: Offers detailed guidance on using LOD expressions for precise and context-independent aggregations.
Tableau Desktop User Guide: Provides comprehensive instructions on managing calculated fields and parameters, ensuring accurate data analysis.
By following these steps, you will have successfully updated the calculation for percent contribution using LOD expressions, providing a more accurate analysis of each manufacturer's contribution to the total quantity. Moreover, updating the parameter with Newell's specific contribution rounds out the task by reflecting precise data inputs for reporting or further analysis.
NEW QUESTION # 28
A client notices that while creating calculated fields, occasionally the new fields are created as strings, integers, or Booleans. The client asks a consultant if there is a performance difference among these three data types.
What should the consultant tell the customer?
Answer: C
Explanation:
In Tableau, the performance of calculated fields can vary based on the data type used. Calculations involving integers and Booleans are generally faster than those involving strings. This is because numerical operations are typically more efficient for a computer to process than string operations, which can be more complex and time-consuming. Therefore, when performance is a consideration, it is advisable to use integers or Booleans over strings whenever possible.
References: The performance hierarchy of data types in Tableau calculations is documented in resources that discuss best practices for optimizing Tableau performance1.
NEW QUESTION # 29
SIMULATION
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.
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.
Answer:
Explanation:
See the complete Steps below in Explanation
Explanation:
To shape the data in the "US Population Estimates" data source and enter the total number of records into the "Total Records" parameter in Tableau Desktop, follow these steps:
Open the CC Workbook and Access the Worksheet:
From the desktop, double-click on the CC workbook to open it in Tableau Desktop.
Navigate to the Population worksheet by selecting its tab at the bottom of the window.
Format and Shape the Data:
Ensure the data types match those specified in the requirements: Sex, Origin, Race as strings; Year, Age, Population as whole numbers.
To verify or change the data type, click on the dropdown arrow next to each field name in the Data pane and select "Change Data Type" if necessary.
Calculate Total Number of Records:
Create a new calculated field named "Total Records". To do this, right-click in the Data pane and select "Create Calculated Field".
Enter the formula COUNT([Record ID]) or SUM([Number of Records]) depending on how the data source identifies each row uniquely.
Drag this new calculated field onto the worksheet to display the total number of records.
Enter the Value into the Total Records Parameter:
Locate the "Total Records" parameter in the Data pane. Right-click on the parameter and select "Edit".
Manually enter the number displayed from the calculated field into the parameter, ensuring accuracy to meet the data shaping requirement.
Save Your Changes:
From the File menu, click 'Save' to ensure all your changes are stored.
References:
Tableau Desktop Guide: Provides detailed instructions on managing data types, creating calculated fields, and updating parameters.
Tableau Data Shaping Techniques: Outlines effective methods for manipulating and structuring data for analysis.
This process will ensure the data in the "US Population Estimates" is accurately shaped according to the specified format and that the total number of records is correctly calculated and entered into the designated parameter. This thorough approach ensures data integrity and accuracy in reporting.
NEW QUESTION # 30
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?
Answer: A
Explanation:
For optimal performance, it is recommended to limit the data to what is necessary for analysis, which in this case would be the current and previous years. Moving the calculation of averages to the data layer and aggregating the dates to a monthly level will reduce the granularity of the data, thereby improving the performance of the dashboard. This approach aligns with best practices for optimizing workbook performance in Tableau, which suggest simplifying the data model and reducing the number of records processed12.
References: The recommendation is based on the guidelines provided in Tableau's official documentation on optimizing workbook performance, which includes tips on data management and aggregation for better performance12.
NEW QUESTION # 31
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?
Answer: C
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.
NEW QUESTION # 32
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