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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Understanding Tableau Concepts | 15% | - Visualization best practices - Workbook, worksheet, and dashboard structure - Dimensions vs measures - Data types and roles |
| Topic 2: Sharing Insights | 25% | - Export and publish visualizations - Set permissions and access - Publish and share workbooks - Ensure accessibility and clarity |
| Topic 3: Exploring and Analyzing Data | 37% | - Create interactive dashboards and stories - Apply calculations and aggregations - Create and customize visualizations - Use filters, parameters, and sets - Sort, group, and summarize data |
| Topic 4: Connecting to and Preparing Data | 23% | - Join and union data - Data cleaning and transformation - Manage data fields and hierarchies - Connect to various data sources |
当社Salesforceのソフトウェアバージョンには、実際のAnalytics-101試験環境をシミュレートするという利点があります。 多くの受験者は、練習をするときにパフォーマンスが正しくなりすぎて緊張するため、JPTestKing実際のAnalytics-101試験に合格できません。 Analytics-101練習資料のこのソフトウェアバージョンは、心理的な恐怖を克服するのに役立ちます。 その上、練習を終えると得点が表示されるので、数回後には間違いなくどんどん良くなります。 Analytics-101試験の受験を完了したため、Salesforce Certified Tableau Desktop Foundations試験に合格する必要があります。
質問 # 24
A Tableau associate needs to share a workbook with a user who does NOT have access to the underlying data.
The user must be able to modify existing visualizations.
What should the associate do?
正解：B
解説：
The associate should save the workbook as a Tableau Packaged Workbook (.twbx). A packaged workbook can contain the workbook itself together with copies of supported local data sources, Tableau extracts, background images, and other workbook resources. This directly addresses the scenario because the recipient does not have access to the original underlying data. When appropriate data is packaged with the workbook, the recipient can open the workbook in Tableau Desktop and interact with or modify its existing worksheets and visualizations without requiring the author's original file paths. A .twb file contains the workbook definition but normally references external data rather than packaging the required local resources. Therefore, it would not reliably solve the access problem. Creating a .hyper file alone provides an extract but does not contain the complete Tableau workbook, including worksheets, dashboards, calculations, formatting, parameters, and visualization definitions. Exporting views produces presentation-oriented outputs and does not satisfy the requirement to modify the existing Tableau visualizations. Tableau specifically recommends packaged workbooks when sharing with someone who does not have access to referenced resources or the original environment.
質問 # 25
A Tableau associate needs to change the color intensity of a quantitative range.
Which option should the associate use?
正解：A
質問 # 26
When should a Tableau associate use a relationship instead of a join for two data sets?
正解：D
解説：
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.
質問 # 27
A Tableau associate has a data set that builds a union between two tables. The associate needs to extract the data set.
What should the associate use to extract the data set?
正解：A
解説：
The correct configuration is Logical tables that use a single table extract, making C correct. In Tableau's data model, a union operates in the physical layer. The two unioned physical tables are merged into one resulting logical table. Tableau explicitly describes logical tables as containers that can contain multiple physical tables joined or unioned together. When an extract is stored using Logical Tables, Tableau creates one extract table for each logical table in the data source. Because the scenario contains one logical table composed of the two unioned physical tables, the extract is consequently represented as a single extract table. This is different from using Physical Tables storage. Physical storage retains an extract table for each physical table and is subject to additional eligibility restrictions. Tableau's current terminology replaced the older "Single Table" and
"Multiple Tables" extract terminology with Logical Tables and Physical Tables, respectively. Official Tableau documentation states that physical tables joined or unioned inside a logical table are merged as part of that logical table, and that Logical Tables extract storage creates one extract table per logical table. Therefore, a two-table union forming one logical table corresponds to a logical/single-table extract structure.
質問 # 28
A Tableau associate is creating a combined axis chart.
Where should the associate drag the second measure after dragging the first measure to the Rows shelf?
正解：B
解説：
Because the first measure is on the Rows shelf, Tableau creates a vertical quantitative axis in the visualization. To construct a combined axis, the associate should drag the second measure directly onto that existing vertical axis, making B correct. A combined axis allows multiple measures to share the same axis instead of displaying them in separate panes or on independent dual axes. When the second measure is dragged onto the existing axis and Tableau displays the appropriate drop indicator, Tableau creates a shared Measure Values-based view containing both measures. The orientation matters. Fields on Rows normally produce a vertical y-axis, whereas fields on Columns normally generate a horizontal x-axis. Consequently, because the first measure was specifically placed on Rows, the target is the vertical axis rather than the horizontal axis. Dropping the second measure on the Marks card would encode that field through a mark property rather than create a combined quantitative axis. Dropping it on Filters would restrict records or values and would not combine the measures. This mechanism should also be distinguished from a dual-axis chart, where two independent axes are layered. A combined axis instead places multiple measures on a shared axis and commonly uses Measure Names and Measure Values for differentiation.
質問 # 29
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