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Salesforce Analytics-DA-201 Exam Syllabus Topics:

Section	Weight	Objectives
Connect to and Transform Data	24%	- Prepare and Transform Data 1. Use Tableau Prep features 2. Create calculated fields and groups 3. Clean and reshape data - Connect to Data Sources 1. Use joins, relationships, and unions 2. Identify and connect to different types of data sources 3. Manage metadata and data properties
Explore and Analyze Data	41%	- Perform Data Analysis 1. Use table calculations and LOD expressions 2. Use sorting, filtering, and grouping 3. Apply aggregations and calculations - Create Visualizations 1. Build charts and dashboards 2. Apply analytics features and forecasting 3. Use maps and geographic analysis
Create Content	26%	- Format and Present Data 1. Improve accessibility and readability 2. Apply formatting and styling - Build Dashboards and Stories 1. Optimize dashboard usability 2. Design interactive dashboards 3. Use actions and parameters
Publish and Manage Content on Tableau Server and Tableau Cloud	9%	- Publish and Share Content 1. Manage permissions and access 2. Schedule refreshes and subscriptions 3. Publish workbooks and data sources

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Salesforce Certified Tableau Data Analyst Sample Questions (Q115-Q120):

NEW QUESTION # 115
A Data Analyst has the following two tables named Orders and Returns.

The analyst needs to get the Customer ID and Customer Name for only the orders that were returned. Orders will be the leading table.
Which type of join should the analyst perform in Tableau Prep?

A. Left join
B. Inner join
C. Full join
D. Unmatched only join

Answer: B

NEW QUESTION # 116
A Data Analyst has the following dataset.

Which grouping option should the analyst use in Tableau Prep to group all five names automatically?

A. Common Characters
B. Spelling
C. Manual Selection
D. Pronunciation

Answer: A

Explanation:
Common Characters is appropriate because the five values contain essentially the same characters but differ in capitalization, punctuation, separators, and-in one case-the order of the first and last names. Tableau Prep's Common Characters fuzzy-matching algorithm removes punctuation, duplicates, and whitespace before evaluating the character fingerprint. Tableau specifically documents that values such as "John Smith" and "Smith, John" can be matched by this technique because their characters are equivalent despite being reordered. Pronunciation is intended for values that sound alike, while Spelling uses edit-distance similarity and is better suited to typographical variations. Manual Selection would require the analyst to choose the values explicitly instead of grouping them automatically. Therefore, B is the verified answer.

NEW QUESTION # 117
A Data Analyst has a data source with row data for service calls and their activity log.

Which calculation allows the analyst to count the calls that have never had a technician assigned to them?

A. SUM({ INCLUDE [Activity Name] : COUNT(IF [Activity Name] < > " Assign Technician " THEN 1 END) })
B. COUNTD(IF { INCLUDE [Activity Name] : NOT " Assign Technician " } THEN [Call ID] END)
C. SUM({ FIXED [Call ID] : IF MAX([Activity Name] = " Assign Technician " ) THEN 0 ELSE 1 END
})
D. COUNT({ FIXED [Call ID] : IF [Activity Name] < > " Assign Technician " THEN 1 ELSE 0 END })

Answer: C

Explanation:
The required logic must first evaluate the activity history independently for each Call ID, which is why a FIXED LOD expression is appropriate. {FIXED [Call ID] : ...} establishes Call ID as the calculation grain regardless of the visualization's dimensions. Within each call, [Activity Name] = " Assign Technician " produces a Boolean condition. Applying MAX to that condition determines whether an assignment activity exists for that call. If one exists, the calculation returns 0; otherwise it returns 1. The outer SUM then totals the calls that never received an assignment. INCLUDE does not provide the required fixed call-level evaluation, while the other expressions either count activity records rather than calls or do not form valid LOD logic for the requirement. Therefore, A is correct.

NEW QUESTION # 118
You have the following dataset.
Which Level of Detail (LOD) expression should you use to calculate tie grand total of all the regions?

A. {FIXED: TOTAL (Sales)}
B. {FIXED: [Region] SUM Sales}
C. {Fixed: [Region]: TOTAL Sales}
D. {FIXED: SUM Sales}

Answer: D

Explanation:
The correct Level of Detail (LOD) expression to calculate the grand total of sales across all regions would be
{SUM(Sales)}. The FIXED expression is not needed here because we are not computing the sum at the level of each region, but rather the total sum across all regions. The FIXED keyword is typically used to aggregate at a certain level regardless of the view.
https://help.tableau.com/current/pro/desktop/en-us/functions_functions_tablecalculation.htm#TOTAL

NEW QUESTION # 119
You have the following line chart that shows the average sales by month.

Which month had the biggest increase in swage sales compared to me previous month in 2019?

A. October
B. December
C. August
D. November

Answer: D

Explanation:
Based on the line chart provided, each point on the line chart represents the average sales for a given month, and the percentage values indicate the change in average sales compared to the previous month. The month of November shows a significant increase from the month of October, indicated by a large upward spike on the chart and a high percentage increase.

NEW QUESTION # 120
......

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