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Salesforce Analytics-DA-201 Exam Syllabus Topics:

Topic	Details
Topic 1	Create Content: This domain involves building visualizations like charts, dashboards, and stories to present data insights clearly. It also focuses on adding interactivity, formatting, and designing responsive dashboards to enhance user experience and data communication.
Topic 2	Publish and Manage Content on Tableau Server and Tableau Cloud: This section covers publishing workbooks, data sources, and flows to Tableau Server or Cloud for sharing and collaboration. It also includes managing content through scheduling refreshes, setting permissions, and creating alerts, subscriptions, and custom views.
Topic 3	Explore and Analyze Data: This section covers creating calculations, applying filters, parameters, and structuring data to explore insights effectively. It also includes advanced analysis techniques such as table calculations, LOD expressions, forecasting, and geographic mapping to derive meaningful patterns and trends.
Topic 4	Connect To and Transform Data: This domain focuses on connecting to various data sources such as files, databases, and published sources, while deciding between live and extract connections. It also covers preparing, cleaning, transforming, and organizing data using Tableau features and Tableau Prep to ensure it is ready for accurate analysis.

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Salesforce Certified Tableau Data Analyst Sample Questions (Q66-Q71):

NEW QUESTION # 66
A Data Analyst has two tables named EmployeeInfo and DepartmentInfo. EmployeeInfo contains four fields named Full Name, Department ID, Start Date, and Salary. DepartmentInfo contains four fields named Department Name, Size, Department ID, and VP. The analyst wants to combine the tables to meet the following requirements:
* EmployeeInfo is the first table that is dragged to the canvas,
* The records must contain the Full Name, and the Department Name, Size, and VP fields if available,
* Not all records have an exact match.
Which type of join should the analyst use?

A. Left
B. Full outer
C. Union
D. Inner

Answer: A

NEW QUESTION # 67
You have the following worksheet.

You want to create a table calculation that shows sales growth over each year.
How should you complete the formula? (Use the dropdowns in the Answer Area to select the correct options to complete the formula.)

Answer:

Explanation:

Explanation:
There are different ways to create a table calculation that shows sales growth over each year, but one possible answer is:
* SUM([Sales])
* LOOKUP(SUM([Sales]), -1)
* PREVIOUS_VALUE(0)
To calculate the sales growth over each year, you need to compare the current year's sales with the previous year's sales and divide the difference by the previous year's sales. You can use the SUM, LOOKUP, and PREVIOUS_VALUE functions to achieve this. The SUM function returns the total sales for each year. The LOOKUP function returns the value of an expression in a target row, specified as a relative offset from the current row. The PREVIOUS_VALUE function returns the value of the expression in the previous row, or a specified value if there is no previous row. The formula for the table calculation is:
(SUM([Sales]) - LOOKUP(SUM([Sales]), -1)) / PREVIOUS_VALUE(0)
This formula subtracts the sales of the previous year (LOOKUP(SUM([Sales]), -1)) from the sales of the current year (SUM([Sales])) and divides the result by the sales of the previous year. If there is no previous year, the formula uses 0 as the denominator (PREVIOUS_VALUE(0)) to avoid division by zero errors.
References:
Tableau Certified Data Analyst Exam Prep Guide, page 11, section "Creating Calculated Fields" Tableau Help: SUM Function Tableau Help: LOOKUP Function Tableau Help: PREVIOUS_VALUE Function

NEW QUESTION # 68
You have a sales dataset that contains the following fields.

You need to analyze the average revenue per product in different regions over time.
Which two fields should be measures? Choose two.

A. Quantity
B. Revenue
C. Order Date
D. Customer Region
E. Product Name

Answer: A,B

Explanation:
To analyze the average revenue per product in different regions over time, you need to use two fields that contain numeric, quantitative values that you can measure and aggregate. Quantity and Revenue are both measures that fit this criterion. You can multiply Quantity and Revenue to get the total sales for each product, and then divide by the number of products to get the average revenue. You can also use these measures to create charts and tables that show the trends and comparisons over time and across regions. References:
* Dimensions and Measures, Blue and Green - Tableau
* Tableau Certified Data Analyst Study Guide

NEW QUESTION # 69
You have the following dataset.

You plan to create a dashboard that will be filtered to show only data that is relevant to a specific Tableau user based on the Tableau_User_Name field You need to create a boolean calculated field to place on the data source finer Which formula should you use for the filter?

A. ISFULLNAMETableu_USER_NAME))=USERNAME()
B. NAMEUSERNAME()
C. NAME Tableau-USER-NAME)
D. USERNAME()=(Tableau_USER_NAME)

Answer: D

Explanation:
To create a boolean calculated field to place on the data source filter, you should use the formula USERNAME() = [Tableau_user]. This formula will return TRUE if the current Tableau user name matches the value in the Tableau_user field, and FALSE otherwise. You can use this formula as a data source filter by dragging it to the Filters shelf and selecting TRUE from the menu. This will filter the data to show only the rows that are relevant to the specific Tableau user.
The other options are not correct for this scenario. NAME([Tableau_user]) is not a valid function in Tableau.
ISFULLNAME([Tableau_user]) = USERNAME() is not a valid expression in Tableau. 'S' + STR([Sales]
/1000) is not a boolean expression, but a string expression that converts sales to thousands with a prefix of
"S". References: https://help.tableau.com/current/pro/desktop/en-us/filtering_datasource.htm https://help.
tableau.com/current/pro/desktop/en-us/functions_functions_logical.htm#USERNAME https://help.tableau.
com/current/pro/desktop/en-us/calculations_calculatedfields.htm
In Tableau, the USERNAME() function returns the username of the user who is currently logged in. To create a filter that only shows data relevant to the logged-in Tableau user, a boolean calculated field can be created to compare the current username with the usernames listed in the Tableau_User_Name field of the dataset. Therefore, the correct formula for this filter is USERNAME() = [Tableau_USER_NAME], which will return true for rows where the Tableau_User_Name matches the current user's username.

NEW QUESTION # 70
You have the following visualization.

The Last() calculation is set to compute using Table (across)
Which value will appear in the crosstab for the Consumer segment of the year 2018 if you change compute to use Oder Dale?

A. 0
B. 1
C. 2
D. 3

Answer: A

Explanation:
The LAST() function in Tableau returns the number of rows from the current row to the last row in the partition. When you compute using ' Order Date ' , it will change the partitioning of the calculation. If ' Consumer ' in ' 2018 ' is the last row in its partition when computed by ' Order Date ' , then LAST() will return
0 for that cell.
The LAST() function in Tableau is a table calculation that returns the number of rows from the current row to the last row in the partition. The value of LAST() is 0 for the last row, increases by 1 for each row above the last row, and can be negative for rows below the current row if there are such rows in the partition.
In the provided visualization, LAST() is set to compute using Table (across). Changing the compute mode to use " Order Date " will adjust the partitioning of the data upon which the LAST() function is calculated. Since
" Order Date " is likely to be a unique value per row (assuming each order has a unique date), each row becomes its own partition.
For the Consumer segment of the year 2018, if " Order Date " is unique for each row, then the last row in each partition (in this case, each individual row) will have a LAST() value of 0 because there are no other rows in the partition - it ' s the last row of its own partition.
Therefore, when you change the compute mode of LAST() to use " Order Date " , each cell under the Consumer segment for the year 2018 will have the LAST() value of 0, because each order date creates a partition of one, making every row the last in its partition.

NEW QUESTION # 71
......

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