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| Section | Objectives |
|---|---|
| Topic 1: Connecting to Data | - Data preparation basics
|
| Topic 2: Exploring and Analyzing Data | - Basic calculations
|
| Topic 3: Understanding Tableau Concepts | - Best practices
|
| Topic 4: Sharing Insights | - Publishing and sharing
|
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問題 #23
When using a data source that has relationships, how can a Tableau associate add a join between two or more tables?
答案：A
解題說明：
To create a join in a data source that already uses relationships, the associate must double-click a logical table in the canvas, making C correct. Tableau's data model has two layers. The top-level logical layer contains logical tables connected by relationships. A join cannot be created directly between these logical tables because joins operate in the underlying physical layer. Double-clicking a logical table opens its physical Join
/Union canvas. From there, the associate can drag or double-click additional physical tables and define the required join clauses and join type. This distinction is fundamental to Tableau's modern data model.
Relationships connect logical tables while keeping them separate and preserving their natural level of detail.
Joins merge physical tables into one logical table using an explicitly defined join configuration. Selecting Add in the Connections pane adds another connection; it does not itself create the join. Dragging a table directly onto the top-level logical canvas generally creates a relationship rather than a physical join. Double-clicking a table in the Tables pane is not the step used to enter the physical layer of an existing logical table. Tableau's official documentation explicitly instructs users to double-click a logical table to open the physical layer where joins and unions can be created.
問題 #24
Which aggregation is available without requiring a table calculation or calculated field?
答案：B
解題說明：
Standard deviation is available as a native aggregation for a measure and does not require the author to create either a table calculation or a calculated field. Therefore, C is correct. When a measure is used in a Tableau view, its aggregation can be changed through the field menu. In addition to commonly used functions such as SUM, AVG, MIN, MAX, and COUNT, Tableau provides Standard Deviation and Standard Deviation (Population) as built-in aggregation choices. The calculation is performed directly over the records contributing to the current mark. Running Total and Percent of Total are different because they are table calculations. They operate on already aggregated values after Tableau has constructed the visualization and depend on the addressing and partitioning of the view. Sample covariance is supported through calculation functionality such as covariance functions but is not presented as the equivalent direct aggregation option in the basic measure aggregation menu represented by this question. Implementing covariance typically involves specifying the two expressions whose covariance is required. Tableau's official Data Aggregation documentation explicitly lists standard deviation among the aggregations available for measures, including sample and population forms. Consequently, it can be selected directly without constructing an additional calculated field or applying a quick table calculation.
問題 #25
Which two statements accurately describe relationships in Tableau Desktop?
答案：C,D
解題說明：
Relationships are designed to preserve each table's level of detail and keep logical tables separate within the data source, making A and B correct. Unlike physical joins, relationships do not flatten participating tables into one combined row-level table when the data source is created. Tableau keeps each logical table distinct and evaluates the relationship dynamically based on fields actually used in a visualization. This architecture helps Tableau analyze data residing at different granularities while reducing the duplication and data-loss risks that can occur with fixed physical joins. Tableau's official relationship documentation explicitly states that relationships maintain each table's native level of detail and create independent domains at multiple granularities. The tables are not merged together in the data source. Option C describes the behavior of joins or unions in the physical layer. Physical tables can be combined to form one logical table, but this is not what a relationship does. Option D is also incorrect because relationships do not require the author to choose a fixed join type such as inner, left, right, or full outer. Tableau determines appropriate joins contextually during analysis. Relevant Tableau Desktop concepts include logical tables, physical tables, relationships, contextual joins, cardinality, and preservation of granularity.
問題 #26
Which string function should a Tableau associate use to find a substring within a column and return a Boolean value?
答案：C
解題說明：
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.
問題 #27
When should a Tableau associate use a relationship instead of a join for two data sets?
答案：B
解題說明：
A relationship is particularly appropriate when the tables being combined contain data at different levels of detail, making D correct. Tableau relationships operate in the logical layer of the data model and preserve each logical table's native granularity. Tableau determines the necessary joins dynamically during analysis according to the fields used in the visualization. This behavior is materially different from a physical join. A join merges records into a single physical table before analysis. If tables have different granularities, a physical join can duplicate measure values or remove records depending on the join structure and matching keys. Relationships reduce that risk because Tableau aggregates relevant information according to each table's natural level of detail before combining results as required by the visualization. Official Tableau guidance explicitly recommends relationships for combining data from different levels of detail. Relationships also preserve independent logical tables rather than flattening them into a single physical table. Option B merely describes where tables reside and does not determine whether a relationship or join is preferable. Options A and C likewise do not identify the principal modeling scenario addressed by relationships. Relevant Tableau Desktop concepts include logical tables, physical tables, relationships, joins, aggregation behavior, and preservation of level of detail.
問題 #28
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