Analytics-101 Study Guide Pdf | Mock Analytics-101 Exams

Salesforce Certified Tableau Desktop Foundations (Analytics-101) Practice exams (desktop and web-based) are designed solely to help you get your Salesforce Certified Tableau Desktop Foundations (Analytics-101) certification on your first try. Our Salesforce Analytics-101 mock test will help you understand the Salesforce Certified Tableau Desktop Foundations (Analytics-101) exam inside out and you will get better marks overall. It is only because you have practical experience of the Salesforce Certified Tableau Desktop Foundations (Analytics-101) exam even before the exam itself.

Salesforce Analytics-101 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Exploring and Analyzing Data37%- Create basic charts
- Organize data and apply filters
- Apply analytics to a worksheet
Topic 2: Connecting to and Preparing Data23%- Create and manage the data model
- Manage data properties
- Create live connections and extracts
Topic 3: Understanding Tableau Concepts15%- Understand discrete and continuous fields
- Understand aggregations
- Understand dimensions and measures
Topic 4: Sharing Insights25%- Format view for presentation
- Create and modify a dashboard
- View and share workbook data

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Salesforce Certified Tableau Desktop Foundations Sample Questions (Q30-Q35):

NEW QUESTION # 30
Which two types of fields appear blue?

Answer: A,B

Explanation:
In Tableau, blue identifies discrete fields, regardless of whether the field is classified as a dimension or a measure. Therefore, both Discrete dimensions and Discrete measures appear blue, making B and C correct.
Tableau separates two different field characteristics. The first is the semantic role: dimension or measure. The second is the behavioral classification: discrete or continuous. These concepts are related but not equivalent.
A discrete field contains distinct values and normally creates headers when added to Rows or Columns.
Tableau represents the pill in blue. Most dimensions are discrete by default, so blue dimensions are common.
Measures are generally continuous, but a measure can be converted to discrete; once it is discrete, its pill also becomes blue. Continuous fields appear green. Continuous dimensions-most commonly continuous date dimensions-and continuous measures therefore use green pills and typically create axes rather than headers.
Tableau's official Dimensions and Measures documentation explicitly presents four valid combinations:
discrete dimensions, continuous dimensions, discrete measures, and continuous measures. It shows discrete dimensions and discrete measures as blue, while both continuous forms are green. This distinction is foundational to predicting how Tableau will structure a visualization.


NEW QUESTION # 31
Which two actions can a Tableau associate perform when joining tables from multiple connections?

Answer: B,D

Explanation:
A multi-connection data source created for a cross-database join can be filtered and can also be converted to or used with an extract, making A and C correct. Cross-database joins allow Tableau to combine tables originating from different supported connections into one logical data source. Tableau supports these joins with either live connections or in-memory extracts. Consequently, the associate can create an extract of the resulting multi-connection data source. Data source filters can also be used to reduce the records Tableau brings into the analytical environment, subject to connector-specific limitations. The other two choices conflict with documented multi-connection restrictions. Tableau explicitly states that stored procedures are not available for multi-connection data sources, eliminating B. A union appends rows from structurally similar tables. In a multi-connection environment, Tableau Desktop requires tables being unioned to come from the same connection; tables from different databases cannot be unioned directly in Tableau Desktop.
Therefore, D does not meet the scenario involving tables across multiple connections. Tableau's official cross- database documentation explains that a cross-database join requires a multi-connection data source, supports both live and extract-based operation, prohibits stored procedures for such sources, and limits unions to tables within the same connection.


NEW QUESTION # 32
A Tableau associate has a bar chart that has a dimension on the Columns shelf and a measure on the Rows shelf.
How can the associate make a stacked bar chart?

Answer: A


NEW QUESTION # 33
Which string function should a Tableau associate use to find a substring within a column and return a Boolean value?

Answer: B

Explanation:
The correct function is CONTAINS, making D correct. Its syntax is conceptually CONTAINS(string, substring), and it returns a Boolean result indicating whether the specified substring exists anywhere within the source string. For example, CONTAINS([Product Name] , "Office") evaluates to TRUE for records where Product Name contains the sequence "Office" and FALSE where it does not. This makes CONTAINS useful for classification calculations, conditional logic, filtering, validation, and text-based segmentation. The other functions perform different operations. RTRIM removes trailing spaces and returns a string. SPLIT separates a string using a delimiter and returns the requested substring component. ENDSWITH does return a Boolean value, but it tests specifically whether the original string ends with the supplied substring. The requirement is to determine whether a substring occurs somewhere within the column value, so ENDSWITH is too restrictive. Tableau's official String Functions reference explicitly defines CONTAINS(string, substring) as returning TRUE when the supplied string contains the specified substring and identifies its output data type as Boolean. The same documentation distinguishes CONTAINS from STARTSWITH, ENDSWITH, trimming functions, and string parsing functions. Relevant topics include calculated fields, string functions, Boolean calculations, and text manipulation.


NEW QUESTION # 34
Which three elements are included in a packaged workbook (.twbx)?

Answer: A,D,E

Explanation:
A Tableau packaged workbook uses the .twbx format to bundle a workbook with supporting local resources needed to use it outside the author's original environment. The correct elements are background images, custom shapes, and extract files. Tableau explicitly lists background images, custom shapes, and Tableau extract files (.hyper) among the resources that can be incorporated into a packaged workbook. These supporting assets are bundled so that another user does not need access to the original local paths used by the workbook author. Other packageable resources include custom geocoding, local cube files, Excel files, Access files, and text-based local data sources. A PDF version of the workbook is not automatically generated and embedded inside a .twbx, making C incorrect. A Tableau Datasource Customization .tdc file is likewise not listed among the standard resources incorporated into a packaged workbook. A .twbx is therefore fundamentally a portable Tableau workbook package rather than simply a workbook definition. This distinction is important when distributing workbooks that depend on local resources. Official Tableau Desktop documentation lists background images, custom shapes, and Tableau extract files among the files included in packaged workbooks.


NEW QUESTION # 35
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