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

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Salesforce Certified Tableau Data Analyst Sample Questions (Q151-Q156):

NEW QUESTION # 151
You have the following dataset:

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

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

Answer: B

Explanation:
Common Characters: Find and group values that have letters or numbers in common. This option uses the ngram fingerprint algorithm that indexes words by their unique characters after removing punctuation, duplicates, and whitespace. This algorithm works for any supported language. This option isn't available for data roles. For example, this algorithm would match names that are represented as "John Smith" and "Smith, John" because they both generate the key "hijmnost". Since this algorithm doesn't consider pronunciation, the value "Tom Jhinois" would have the same key "hijmnost" and would also be included in the group.

NEW QUESTION # 152
A Data Analyst has the following primary data source that contairis a dimension named Dorm_Code.

The analyst receives the following secondary data source that contains updated dorm codes.

The analyst needs to bring the updated dorm codes into Tableau and use the codes in existing visualizations.
The new dorm codes must use the existing field name of Dorm_Code.
What should the analyst do?

A. Bring in the secondary table as a left join to the primary data source. From the Data Source page, select Create Calculated Field in the Dorm_Name field and enter [Dorm_Name_New] in the calculation window.
B. Create a data blend and select Edit Primary Aliases to replace the primary data source alias values with values from the secondary data source.
C. Bring in the secondary data source by using relationships. From the Data pane, right-click Dorm_Name, select Replace References, and then select Dorm Name New.
D. Bring in the secondary data source as a union.

Answer: C

NEW QUESTION # 153
You plan to create a Tableau subscription for several users.
Which two formats can you use? Choose two.

A. Image
B. Microsoft PowerPoint
C. PDF
D. Microsoft Excel

Answer: A,C

NEW QUESTION # 154
in which three formats can you export a worksheet from the Worksheet menu? Choose three

A. .pptx
B. .png
C. .csv
D. .html
E. .txt
F. .xlsx

Answer: A,B,F

Explanation:
Tableau provides various options to export data from a worksheet. The formats available are typically those that are best suited for visualization or further data analysis. The options include:
* .png for exporting images of the visualizations
* .xlsx for exporting data in a format that can be opened with Microsoft Excel
* .pptx for creating PowerPoint presentations with the visualization embedded These formats are designed to facilitate sharing and presenting the insights derived from Tableau visualizations, or for conducting further analysis in tools like Excel.

NEW QUESTION # 155
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. SUM({ FIXED [Call ID] : IF MAX([Activity Name] = " Assign Technician " ) THEN 0 ELSE 1 END
})
C. COUNT({ FIXED [Call ID] : IF [Activity Name] < > " Assign Technician " THEN 1 ELSE 0 END })
D. COUNTD(IF { INCLUDE [Activity Name] : NOT " Assign Technician " } THEN [Call ID] END)

Answer: B

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 # 156
......

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