CertShikenを選ぶかどうか状況があれば、弊社の無料なサンプルをダウンロードしてから、決めても大丈夫です。こうして、弊社の商品はどのくらいあなたの力になるのはよく分かっています。CertShikenはSalesforce Analytics-101認証試験を助けって通じての最良の選択で、１００％のSalesforce Analytics-101認証試験合格率のはCertShiken最高の保証でございます。君が選んだのはCertShiken、成功を選択したのに等しいです。
| Section | Objectives |
|---|---|
| Understanding Tableau Concepts | - Best practices
|
| Exploring and Analyzing Data | - Building views
|
| Connecting to Data | - Data sources and connections
|
| Sharing Insights | - Dashboards
|
複雑な知識が簡素化され、学習内容が習得しやすいAnalytics-101テストトレントのセットを提供します。これにより、貴重な時間を制限しながら、より重要な知識を獲得できます。当社のAnalytics-101ガイドトレントには、計時機能とシミュレーションテスト機能が装備されています。タイムキーパーを設定して、速度を調整し、効率を改善するために注意を払うのに役立ちます。当社の専門家チームは、Analytics-101認定トレーニングでAnalytics-101試験を準備するのに20〜30時間しかかからない非常に効率的なトレーニングプロセスを設計しました。
質問 # 15
Which chart type uses automatically generated sizes that cannot be resized by using the Marks card?
正解：A
解説：
The correct answer is Treemaps. A treemap represents data as a set of rectangles. Tableau uses one or more dimensions to define the rectangular structure, while a measure placed on Size determines each rectangle's relative area. Tableau automatically lays out the rectangles to use the available visualization space efficiently.
The analyst therefore controls relative size through the measure encoded on Size rather than manually resizing the generated rectangles with the ordinary Marks card size slider. For example, if Sub-Category defines the rectangles and Sales is placed on Size, categories with larger aggregated Sales values receive proportionally larger rectangles. Changing the Sales values or replacing the field on Size changes the relative areas, while Tableau recalculates the layout automatically. Pie charts have mark-size controls and can be resized through the Marks card. Area charts derive their visual area from their axes and underlying measures. Histograms use bars representing bins and frequencies and have different bar-sizing behavior. Tableau's official Treemap documentation identifies Size and Color as the crucial encodings and explains that a measure on Size determines the areas of the rectangles. The resulting treemap geometry is automatically laid out according to those values rather than manually sized mark by mark.
質問 # 16
Which three elements are included in a packaged workbook (.twbx)?
正解：B、C、D
解説：
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.
質問 # 17
Which two actions can a Tableau associate perform when joining tables from multiple connections?
正解：B、D
解説：
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.
質問 # 18
A Tableau associate has the following data.
The associate wants to sort each category's sub-category by ascending sales.
Which sort option should the associate use?
正解：A
解説：
The correct option is Nested because the Sub-category members must be sorted independently within each Category based on Sales. A nested sort evaluates the measure separately inside each pane or parent dimensional grouping. In this example, the Home sub-categories should be sorted according to their Home Sales values, while the Bath sub-categories must be sorted independently according to the Bath Sales values.
For Home, Bulk has Sales of $50 and Accessory has $60, so ascending order is Bulk followed by Accessory.
For Bath, Accessory has $45 and Bulk has $75, so ascending order is Accessory followed by Bulk. This demonstrates why a single global ordering is insufficient: the correct Sub-category order differs between the two Category groups. A non-nested field sort can produce a consistent order based on aggregated values across the view, which would not satisfy the requirement to rank Sub-category independently inside each Category. Manual sorting would require explicit maintenance, while data source order simply follows the ordering supplied by the underlying source. Tableau's official sorting documentation states that nested sorting considers values independently per pane and sorts the values separately within those panes.
質問 # 19
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?
正解：C
解説：
To convert the existing bar chart into a stacked bar chart, the associate should drag another dimension to Color on the Marks card. The initial bar chart already contains a dimension on Columns and a measure on Rows. Adding another categorical dimension to Color partitions each bar according to the members of that second dimension. Tableau assigns a separate color to each resulting group and, because automatic stacking is enabled for bar marks by default, those groups are displayed cumulatively within each bar. For example, if Category is on Columns and SUM(Sales) is on Rows, adding Segment to Color divides each Category bar into Consumer, Corporate, and Home Office segments while preserving the bar's total Sales magnitude.
Dragging another dimension to Size changes the visual size encoding rather than creating standard stacked segments. Adding another measure to Rows typically introduces an additional axis or measure structure. A measure placed on Color generally creates a quantitative gradient rather than categorical stacked segments.
Tableau's official Stack Marks documentation describes this exact construction: a dimension on Columns, a measure on Rows, and another dimension used to color-encode the marks.
質問 # 20
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