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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Sharing Insights | 25% | - Publish and share workbooks - Export and publish visualizations - Ensure accessibility and clarity - Set permissions and access |
| Topic 2: Connecting to and Preparing Data | 23% | - Manage data fields and hierarchies - Join and union data - Data cleaning and transformation - Connect to various data sources |
| Topic 3: Understanding Tableau Concepts | 15% | - Workbook, worksheet, and dashboard structure - Dimensions vs measures - Data types and roles - Visualization best practices |
| Topic 4: Exploring and Analyzing Data | 37% | - Apply calculations and aggregations - Create interactive dashboards and stories - Sort, group, and summarize data - Create and customize visualizations - Use filters, parameters, and sets |
>> Analytics-101최신 덤프샘플문제 다운 <<
Salesforce Analytics-101인증시험은 전문적인 관련지식을 테스트하는 인증시험입니다. Itcertkr는 여러분이Salesforce Analytics-101인증시험을 통과할 수 잇도록 도와주는 사이트입니다. 많은 분들이 많은 시간과 돈을 들여 혹은 여러 학원 등을 다니면서Salesforce Analytics-101인증시험패스에 노력을 다합니다. 하지만 우리Itcertkr에서는 20시간 좌우만 투자하면 무조건Salesforce Analytics-101시험을 패스할 수 있도록 도와드립니다.
질문 # 26
At a minimum, what does a Tableau associate need to create a simple scatter plot?
정답：D
설명：
A basic scatter plot requires one measure on Columns and another measure on Rows, so D is correct. A scatter plot displays the relationship between two quantitative variables. One measure determines the horizontal position of each mark, while the second measure determines its vertical position. For example, placing SUM(Sales) on Columns and SUM(Profit) on Rows establishes a two-dimensional quantitative coordinate system. A dimension may then be added to Detail, Color, Shape, or another Marks property to create separate marks for entities such as customers, products, or states. However, that additional dimension is not the fundamental axis requirement identified by the question. The minimum structural requirement is two quantitative measures defining the x- and y-axes. A dimension plus a measure normally produces a categorical view such as a bar chart rather than a scatter plot. Two dimensions likewise do not supply the pair of quantitative scales required to analyze numerical correlation or distribution. Tableau's visual construction model distinguishes continuous quantitative measures, which generate axes, from discrete fields, which generally create headers. A scatter plot relies on two quantitative axes and therefore requires measures on both Rows and Columns. This is consistent with Tableau's standard scatter-plot construction methodology and its continuous-field behavior.
질문 # 27
Which three statements accurately describe dimensions?
정답：A,C,E
설명：
Dimensions are fields Tableau uses primarily to categorize, segment, and describe data. They typically contain qualitative information such as names, geographic locations, categories, dates, and identifiers.
Therefore, C is correct. Tableau also states that dimensions affect the level of detail in a visualization. Adding another dimension can partition existing marks into more granular groups because Tableau incorporates the field's members into the view's dimensional structure. Therefore, B is correct. The dimension/measure classification is independent from the discrete/continuous classification. Although dimensions are commonly discrete, a dimension can also be continuous. Date fields are a standard example: a date may be represented as a discrete date part or a continuous date value. Therefore, E is correct. Option D instead describes measures, which generally contain quantitative numeric values and are aggregated. Option A is not an inherent defining characteristic of dimensions; formatting behavior depends on how a field is used and whether it is discrete or continuous. Official Tableau guidance identifies dimensions as qualitative fields that group or segment data and explicitly states that dimensions affect the level of detail in the view.
질문 # 28
A Tableau associate wants to assign the Latitude geographic role to a field.
What should be the data type and the data role of the field?
Choose two options.
정답：A,C
설명：
For a standard custom latitude field, Tableau recommends a Number (decimal) data type and a Measure data role. Therefore, A and B are correct. Latitude represents a numeric coordinate, including fractional values such as 40.7128, so Number (decimal) is the appropriate data type. Treating latitude as a measure enables Tableau to position coordinate values continuously on an axis rather than interpreting each coordinate as an independent categorical member. Tableau's official mapping guidance states that, in most cases, latitude and longitude fields should have a data type of Number (decimal), a data role of Measure, and the corresponding Latitude or Longitude geographic role. When used in a map, Longitude is normally placed on Columns and Latitude on Rows as continuous measures. This differs from geographic fields such as Country, State, or City, which are usually string dimensions. Although specialized mapping scenarios can convert latitude or longitude to dimensions, that is not the standard configuration addressed by this question. The official Tableau mapping documentation explicitly specifies the Number (decimal) + Measure configuration for latitude and longitude fields when preparing geographic data for mapping.
질문 # 29
Which chart type uses automatically generated sizes that cannot be resized by using the Marks card?
정답：B
설명：
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.
질문 # 30
Which two actions can a Tableau associate perform when joining tables from multiple connections?
정답：C,D
설명：
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.
질문 # 31
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