{"id":23356,"date":"2026-09-28T05:11:04","date_gmt":"2026-09-28T05:11:04","guid":{"rendered":"https:\/\/www.examlabs.com\/certification\/?p=23356"},"modified":"2026-09-28T05:11:04","modified_gmt":"2026-09-28T05:11:04","slug":"tableau-tda-c01-practice-test-questions-and-exam-dumps-part19-q361-380","status":"publish","type":"post","link":"https:\/\/www.examlabs.com\/certification\/tableau-tda-c01-practice-test-questions-and-exam-dumps-part19-q361-380\/","title":{"rendered":"Tableau TDA-C01 Practice Test Questions and Exam Dumps Part19 Q361-380"},"content":{"rendered":"

View Full <\/b>Tableau TDA-C01 Exam Dumps<\/b><\/a> and Practice Test Dumps<\/b><\/h2>\n

 <\/p>\n

Question 361.<\/b><\/p>\n

An analyst wants to display the top 10 customers by Sales, but only within the currently selected Product Category. Which Tableau configuration is most appropriate?<\/b><\/p>\n

    \n
  1. <\/b> Make Product Category a context filter, then apply a Top 10 Customer filter based on SUM(Sales)<\/span>
    \n<\/span>2.<\/b> Apply the Top 10 Customer filter and then convert Product Category to a measure<\/span>
    \n<\/span>3.<\/b> Use a highlight action instead of filtering<\/span>
    \n<\/span>4.<\/b> Create a histogram using Customer Name<\/span><\/li>\n<\/ol>\n

    Correct Answer: 1<\/b><\/p>\n

    Explanation:<\/b><\/p>\n

    A context filter establishes a subset of the data before later filters are evaluated. If Product Category is made a context filter, Tableau first limits the data to the selected category. The Top 10 Customer filter can then identify the highest-selling customers within that subset. Without the context filter, Tableau may identify the top customers across a broader population and then apply the category restriction afterward. This is a classic example of Tableau\u2019s order of operations affecting analytical results. Highlight actions and histograms do not provide the required Top N filtering behavior.<\/span><\/p>\n

    Question 362.<\/b><\/p>\n

    Which Tableau filter type is most appropriate for keeping only marks where aggregated Profit is greater than zero?<\/b><\/p>\n

      \n
    1. <\/b> Extract filter<\/span>
      \n<\/span>2.<\/b> Measure filter<\/span>
      \n<\/span>3.<\/b> Context filter only<\/span>
      \n<\/span>4.<\/b> Data source filter<\/span><\/li>\n<\/ol>\n

      Correct Answer: 2<\/b><\/p>\n

      Explanation:<\/b><\/p>\n

      A measure filter operates on aggregated quantitative results such as SUM(Profit), AVG(Sales), or COUNT(Order ID). If the view contains dimensions such as Category and the analyst wants to keep only categories whose aggregated Profit is positive, a measure filter on SUM(Profit) is appropriate. Extract and data source filters restrict rows much earlier in Tableau\u2019s processing order and would not directly evaluate the final aggregate per mark. Context filters establish a subset for later operations. When the filtering condition specifically depends on the result of an aggregation, a measure filter is generally the correct choice.<\/span><\/p>\n

      Question 363.<\/b><\/p>\n

      An analyst needs a calculation that returns total Sales at the Region level even when State and City are added to the worksheet. Which expression should be used?<\/b><\/p>\n

        \n
      1. <\/b> { INCLUDE [Region] : SUM([Sales]) }<\/span>
        \n<\/span>2.<\/b> { EXCLUDE [Region] : SUM([Sales]) }<\/span>
        \n<\/span>3.<\/b> { FIXED [Region] : SUM([Sales]) }<\/span>
        \n<\/span>4.<\/b> RUNNING_SUM(SUM([Sales]))<\/span><\/li>\n<\/ol>\n

        Correct Answer: 3<\/b><\/p>\n

        Explanation:<\/b><\/p>\n

        A FIXED level-of-detail expression calculates an aggregation at the dimensions explicitly named in the expression. <\/span>{ FIXED [Region] : SUM([Sales]) }<\/span> therefore produces a Region-level total even when lower-level geographic dimensions such as State or City are added to the visualization. INCLUDE operates relative to the current view and adds finer detail, while EXCLUDE removes specified dimensions. Running Total is a table calculation evaluated on displayed marks. FIXED is useful when a metric must remain at a defined grain independently of most dimensions in the view, although Tableau\u2019s filter order still determines which filters affect it.<\/span><\/p>\n

        Question 364.<\/b><\/p>\n

        Which Tableau LOD expression type is designed to remove a dimension currently present in the view from a particular calculation?<\/b><\/p>\n

          \n
        1. <\/b> FIXED<\/span>
          \n<\/span>2.<\/b> INCLUDE<\/span>
          \n<\/span>3.<\/b> WINDOW<\/span>
          \n<\/span>4.<\/b> EXCLUDE<\/span><\/li>\n<\/ol>\n

          Correct Answer: 4<\/b><\/p>\n

          Explanation:<\/b><\/p>\n

          EXCLUDE removes one or more dimensions from the level of detail used for an LOD calculation. For example, if Category and Sub-Category are both displayed, an EXCLUDE expression can ignore Sub-Category and calculate a broader Category-level value. This is useful for comparing detailed marks with parent-level totals while keeping the detail visible. INCLUDE performs the opposite behavior by adding dimensions to the calculation grain. FIXED defines an explicit level of detail independent of most dimensions in the view. EXCLUDE is therefore the natural choice when the calculation should ignore a displayed dimension.<\/span><\/p>\n

          Question 365.<\/b><\/p>\n

          A worksheet displays Region but not Customer. The analyst wants to calculate Sales at the Customer level before averaging those results by Region. Which LOD expression type is appropriate?<\/b><\/p>\n

            \n
          1. <\/b> INCLUDE<\/span>
            \n<\/span>2.<\/b> EXCLUDE<\/span>
            \n<\/span>3.<\/b> Running Total<\/span>
            \n<\/span>4.<\/b> Rank<\/span><\/li>\n<\/ol>\n

            Correct Answer: 1<\/b><\/p>\n

            Explanation:<\/b><\/p>\n

            INCLUDE adds a dimension to the calculation\u2019s level of detail even if that dimension is not displayed. By including Customer ID, Tableau can first calculate customer-level Sales and then aggregate those values at the Region level. This pattern is useful for metrics such as average customer value, where simply applying AVG to transaction-level Sales may produce the wrong business result. EXCLUDE removes dimensions rather than adding them, while Running Total and Rank are table calculations based on marks already present in the view. INCLUDE is specifically designed for introducing finer hidden granularity into an LOD calculation.<\/span><\/p>\n

            Question 366.<\/b><\/p>\n

            Which Tableau table calculation should an analyst use to show cumulative Sales from the beginning of the year through each month?<\/b><\/p>\n

              \n
            1. <\/b> Difference<\/span>
              \n<\/span>2.<\/b> Running Total<\/span>
              \n<\/span>3.<\/b> Percent Difference<\/span>
              \n<\/span>4.<\/b> Rank<\/span><\/li>\n<\/ol>\n

              Correct Answer: 2<\/b><\/p>\n

              Explanation:<\/b><\/p>\n

              Running Total accumulates an aggregated measure as Tableau progresses through the marks in the specified addressing direction. If Month is ordered chronologically, applying Running Total to SUM(Sales) creates a year-to-date Sales value for each month. The analyst should configure Compute Using so that the calculation moves across Month and restarts for each Year when multiple years are present. Difference and Percent Difference measure period-to-period change, while Rank assigns positions. For cumulative performance analysis, Running Total is the appropriate quick table calculation.<\/span><\/p>\n

              Question 367.<\/b><\/p>\n

              Which Tableau table calculation is most appropriate for showing each month\u2019s Sales as a percentage of the total Sales for the year?<\/b><\/p>\n

                \n
              1. <\/b> Running Total<\/span>
                \n<\/span>2.<\/b> Difference<\/span>
                \n<\/span>3.<\/b> Percent of Total<\/span>
                \n<\/span>4.<\/b> Rank<\/span><\/li>\n<\/ol>\n

                Correct Answer: 3<\/b><\/p>\n

                Explanation:<\/b><\/p>\n

                Percent of Total divides each mark by the total value for the current table-calculation partition. If the partition represents one year and Month is the addressing dimension, Tableau can display each month\u2019s contribution to annual Sales. Correct partitioning is essential because the denominator depends on which marks Tableau considers part of the total. Running Total accumulates values, Difference compares one mark with another, and Rank orders marks by measure value. Percent of Total is the appropriate calculation when the analytical question concerns relative contribution to an overall total.<\/span><\/p>\n

                Question 368.<\/b><\/p>\n

                Which Tableau function can retrieve the Sales value from the immediately preceding row in the current table-calculation partition?<\/b><\/p>\n

                  \n
                1. <\/b> INDEX()<\/span>
                  \n<\/span>2.<\/b> SIZE()<\/span>
                  \n<\/span>3.<\/b> FIRST()<\/span>
                  \n<\/span>4.<\/b> LOOKUP(SUM([Sales]),-1)<\/span><\/li>\n<\/ol>\n

                  Correct Answer: 4<\/b><\/p>\n

                  Explanation:<\/b><\/p>\n

                  LOOKUP()<\/span> retrieves the value of an expression from another mark at a relative offset. An offset of <\/span>-1<\/span> references the immediately preceding mark, assuming the view is sorted and addressed correctly. For example, <\/span>LOOKUP(SUM([Sales]),-1)<\/span> can return the previous month\u2019s Sales in a monthly time series. This supports custom difference, growth, and comparison calculations. INDEX returns positional numbering, SIZE returns partition length, and FIRST returns the offset to the first row. LOOKUP is the correct function when a calculation needs direct access to a neighboring mark\u2019s value.<\/span><\/p>\n

                  Question 369.<\/b><\/p>\n

                  Which Tableau table-calculation function returns the sequential position of the current mark within a partition?<\/b><\/p>\n

                    \n
                  1. <\/b> INDEX()<\/span>
                    \n<\/span>2.<\/b> SIZE()<\/span>
                    \n<\/span>3.<\/b> RANK_PERCENTILE()<\/span>
                    \n<\/span>4.<\/b> WINDOW_SUM()<\/span><\/li>\n<\/ol>\n

                    Correct Answer: 1<\/b><\/p>\n

                    Explanation:<\/b><\/p>\n

                    INDEX()<\/span> returns the sequential position of each mark within the table-calculation partition, beginning at 1. It is based on the current ordering of the marks rather than on their measure values. INDEX is useful for row numbering, advanced table-calculation logic, or filtering specific positional ranges. Changing the sort order or Compute Using configuration may change the returned values. SIZE reports the number of marks in the partition, while RANK_PERCENTILE and WINDOW_SUM perform different analytical calculations. When simple positional numbering is required, INDEX is the appropriate function.<\/span><\/p>\n

                    Question 370.<\/b><\/p>\n

                    Which Tableau function returns the total number of marks in the current table-calculation partition?<\/b><\/p>\n

                      \n
                    1. <\/b> COUNT()<\/span>
                      \n<\/span>2.<\/b> SIZE()<\/span>
                      \n<\/span>3.<\/b> INDEX()<\/span>
                      \n<\/span>4.<\/b> ATTR()<\/span><\/li>\n<\/ol>\n

                      Correct Answer: 2<\/b><\/p>\n

                      Explanation:<\/b><\/p>\n

                      SIZE()<\/span> returns the number of marks in the active table-calculation partition. This can be useful in calculations that behave differently depending on partition length or when determining whether enough observations exist for a rolling analysis. The result depends on how Tableau partitions the view, so changing dimensions or Compute Using can change the value. COUNT operates on underlying data values rather than simply reporting partition size. INDEX returns a mark\u2019s position, while ATTR evaluates whether a single value represents the underlying records. SIZE specifically describes the number of displayed marks participating in the partition.<\/span><\/p>\n

                      Question 371.<\/b><\/p>\n

                      An analyst wants to smooth monthly Sales fluctuations by showing the average of the current month and the previous two months. Which Tableau feature is most appropriate?<\/b><\/p>\n

                        \n
                      1. <\/b> FIXED LOD expression<\/span>
                        \n<\/span>2.<\/b> Reference line<\/span>
                        \n<\/span>3.<\/b> Moving Average table calculation<\/span>
                        \n<\/span>4.<\/b> Data source filter<\/span><\/li>\n<\/ol>\n

                        Correct Answer: 3<\/b><\/p>\n

                        Explanation:<\/b><\/p>\n

                        A Moving Average table calculation computes an average across a rolling window of marks. For a three-month moving average, the analyst can configure the calculation to include the current month and two preceding months. This helps reduce short-term noise and makes broader patterns easier to identify. Because it operates on displayed aggregated marks, the chronological ordering and Compute Using settings are important. FIXED LOD expressions control aggregation granularity, reference lines display benchmarks, and data source filters restrict records. Moving Average is the most appropriate feature for rolling smoothing of a time series.<\/span><\/p>\n

                        Question 372.<\/b><\/p>\n

                        Which Tableau function is best for converting a null numeric result to zero?<\/b><\/p>\n

                          \n
                        1. <\/b> ISNULL()<\/span>
                          \n<\/span>2.<\/b> COUNT()<\/span>
                          \n<\/span>3.<\/b> ATTR()<\/span>
                          \n<\/span>4.<\/b> ZN()<\/span><\/li>\n<\/ol>\n

                          Correct Answer: 4<\/b><\/p>\n

                          Explanation:<\/b><\/p>\n

                          ZN()<\/span> returns zero when a numeric expression is null and otherwise returns the original numeric value. It can simplify calculations when the intended business meaning of missing numeric data is zero. However, analysts should apply it carefully because a true zero and an unknown or missing value are not always equivalent. ISNULL only tests whether a value is null, while COUNT and ATTR are aggregation functions with different purposes. ZN is specifically designed for null-to-zero conversion of numeric expressions and is therefore the most direct choice.<\/span><\/p>\n

                          Question 373.<\/b><\/p>\n

                          Which Tableau function should be used when a null text value should be replaced with the string <\/b>Unknown<\/b>?<\/b><\/p>\n

                            \n
                          1. <\/b> IFNULL([Field],”Unknown”)<\/span>
                            \n<\/span>2.<\/b> ZN([Field])<\/span>
                            \n<\/span>3.<\/b> COUNTD([Field])<\/span>
                            \n<\/span>4.<\/b> ATTR([Field])<\/span><\/li>\n<\/ol>\n

                            Correct Answer: 1<\/b><\/p>\n

                            Explanation:<\/b><\/p>\n

                            IFNULL()<\/span> returns the original expression when it is populated and a replacement value when the expression is null. For a text field, <\/span>IFNULL([Field],”Unknown”)<\/span> provides a clear label for missing values. ZN is intended specifically for numeric values and replaces null with zero. COUNTD counts distinct field values, while ATTR checks whether one consistent value represents the underlying records. IFNULL is useful when missing text, dates, or other compatible values should be replaced with a defined fallback in a calculated field.<\/span><\/p>\n

                            Question 374.<\/b><\/p>\n

                            Which Tableau function should an analyst use to test whether a string begins with <\/b>CUS-<\/b>?<\/b><\/p>\n

                              \n
                            1. <\/b> CONTAINS()<\/span>
                              \n<\/span>2.<\/b> STARTSWITH()<\/span>
                              \n<\/span>3.<\/b> ENDSWITH()<\/span>
                              \n<\/span>4.<\/b> FIND()<\/span><\/li>\n<\/ol>\n

                              Correct Answer: 2<\/b><\/p>\n

                              Explanation:<\/b><\/p>\n

                              STARTSWITH()<\/span> returns TRUE when a string begins with the specified substring. For example, <\/span>STARTSWITH([Customer Code],”CUS-“)<\/span> can classify values that follow a customer-code naming standard. CONTAINS checks whether the substring appears anywhere, while ENDSWITH tests only the end of the string. FIND returns the position of a substring and can be used for more complex parsing, but STARTSWITH communicates the intended rule more directly. Purpose-specific string functions make calculated fields easier to read and maintain.<\/span><\/p>\n

                              Question 375.<\/b><\/p>\n

                              Which Tableau function should be used to determine whether a Product Description contains the word <\/b>Premium<\/b> anywhere in the text?<\/b><\/p>\n

                                \n
                              1. <\/b> LEFT()<\/span>
                                \n<\/span>2.<\/b> RIGHT()<\/span>
                                \n<\/span>3.<\/b> CONTAINS()<\/span>
                                \n<\/span>4.<\/b> LEN()<\/span><\/li>\n<\/ol>\n

                                Correct Answer: 3<\/b><\/p>\n

                                Explanation:<\/b><\/p>\n

                                CONTAINS()<\/span> returns TRUE when the specified substring occurs anywhere within another string. For example, <\/span>CONTAINS([Product Description],”Premium”)<\/span> can identify products whose descriptions include that word regardless of where it appears. LEFT and RIGHT extract characters from the beginning or end, while LEN reports the number of characters. CONTAINS is especially useful for classification, filtering, and Boolean flags when the important text can appear at any position within a descriptive field.<\/span><\/p>\n

                                Question 376.<\/b><\/p>\n

                                Which Tableau function can replace all occurrences of a known substring inside another string?<\/b><\/p>\n

                                  \n
                                1. <\/b> TRIM()<\/span>
                                  \n<\/span>2.<\/b> MID()<\/span>
                                  \n<\/span>3.<\/b> FIND()<\/span>
                                  \n<\/span>4.<\/b> REPLACE()<\/span><\/li>\n<\/ol>\n

                                  Correct Answer: 4<\/b><\/p>\n

                                  Explanation:<\/b><\/p>\n

                                  REPLACE()<\/span> substitutes occurrences of one substring with another in a text value. For example, an analyst could replace a repeated abbreviation with its full business term or remove a known unwanted character by replacing it with an empty string. The transformation applies within Tableau and does not permanently modify the source data. TRIM removes leading and trailing spaces, MID extracts characters from an internal position, and FIND identifies the position of text. REPLACE is the appropriate function for predictable search-and-substitute text cleanup.<\/span><\/p>\n

                                  Question 377.<\/b><\/p>\n

                                  An analyst wants to calculate the number of days between Order Date and Ship Date. Which expression is most appropriate?<\/b><\/p>\n

                                    \n
                                  1. <\/b> DATEDIFF(‘day’,[Order Date],[Ship Date])<\/span>
                                    \n<\/span>2.<\/b> DATEADD(‘day’,[Order Date],[Ship Date])<\/span>
                                    \n<\/span>3.<\/b> DATETRUNC(‘day’,[Order Date])<\/span>
                                    \n<\/span>4.<\/b> DAY([Order Date])+DAY([Ship Date])<\/span><\/li>\n<\/ol>\n

                                    Correct Answer: 1<\/b><\/p>\n

                                    Explanation:<\/b><\/p>\n

                                    DATEDIFF()<\/span> calculates the difference between two date values in a specified date unit. Using <\/span>‘day’<\/span> returns the number of day boundaries between Order Date and Ship Date and is commonly used for shipping time, resolution time, or customer tenure calculations. DATEADD shifts a date by an interval, while DATETRUNC reduces a date to the beginning of a specified period. Adding day components does not calculate elapsed time correctly. DATEDIFF is therefore the appropriate function when the requirement is to quantify the interval between two dates.<\/span><\/p>\n

                                    Question 378.<\/b><\/p>\n

                                    Which Tableau function should be used to return a date that is exactly one month after Order Date?<\/b><\/p>\n

                                      \n
                                    1. <\/b> DATEDIFF()<\/span>
                                      \n<\/span>2.<\/b> DATEADD(‘month’,1,[Order Date])<\/span>
                                      \n<\/span>3.<\/b> DATETRUNC()<\/span>
                                      \n<\/span>4.<\/b> MONTH()<\/span><\/li>\n<\/ol>\n

                                      Correct Answer: 2<\/b><\/p>\n

                                      Explanation:<\/b><\/p>\n

                                      DATEADD()<\/span> moves a date forward or backward by a specified number of date units. <\/span>DATEADD(‘month’,1,[Order Date])<\/span> returns a date one month after each Order Date. This properly handles transitions across years and month boundaries. DATEDIFF measures the interval between dates, while DATETRUNC reduces a date to a time-period boundary. MONTH extracts the month component. DATEADD is appropriate for renewal dates, follow-up dates, expiration periods, and other business rules involving date offsets.<\/span><\/p>\n

                                      Question 379.<\/b><\/p>\n

                                      A data model contains a detailed Orders table and a monthly Targets table at a different grain. Which Tableau approach can help preserve each table’s level of detail rather than physically duplicating target values across order rows?<\/b><\/p>\n

                                        \n
                                      1. <\/b> Union<\/span>
                                        \n<\/span>2.<\/b> Physical join only<\/span>
                                        \n<\/span>3.<\/b> Relationship<\/span>
                                        \n<\/span>4.<\/b> Bin<\/span><\/li>\n<\/ol>\n

                                        Correct Answer: 3<\/b><\/p>\n

                                        Explanation:<\/b><\/p>\n

                                        Relationships operate in Tableau\u2019s logical layer and allow each logical table to preserve its natural level of detail. Tableau determines how to combine the data depending on which fields are used in the visualization. This can help avoid problems that occur when a monthly Targets table is physically joined to a highly detailed Orders table, potentially repeating target values across many order rows. Relationships still require correct matching fields and sound data modeling. A union stacks rows, while bins group numerical values. For tables with different grains, relationships are often the more appropriate modeling choice.<\/span><\/p>\n

                                        Question 380.<\/b><\/p>\n

                                        A dashboard user selects a Product Category in one chart, and the analyst wants several other worksheets to display only records from that category. Which feature should be configured?<\/b><\/p>\n

                                          \n
                                        1. <\/b> Highlight action<\/span>
                                          \n<\/span>2.<\/b> Parameter action<\/span>
                                          \n<\/span>3.<\/b> URL action<\/span>
                                          \n<\/span>4.<\/b> Filter action<\/span><\/li>\n<\/ol>\n

                                          Correct Answer: 4<\/b><\/p>\n

                                          Explanation:<\/b><\/p>\n

                                          A filter action uses values selected in a source worksheet to restrict the data shown in one or more target worksheets. Selecting a Product Category can therefore cause related tables, maps, and charts to display only records associated with that category. This creates intuitive dashboard interactivity because the visualization itself functions as a filter control. Highlight actions preserve unrelated marks and only emphasize matching ones. Parameter actions update parameter values, while URL actions open external pages. When unrelated records should be removed from target views based on a selection, a filter action is the correct Tableau feature.<\/span><\/p>\n

                                           <\/p>\n","protected":false},"excerpt":{"rendered":"

                                          View Full Tableau TDA-C01 Exam Dumps and Practice Test Dumps   Question 361. An analyst wants to display the top 10 customers by Sales, but only within the currently selected Product Category. Which Tableau configuration is most appropriate? Make Product Category a context filter, then apply a Top 10 Customer filter based on SUM(Sales) 2. […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[1648,1647],"tags":[],"_links":{"self":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/23356"}],"collection":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/comments?post=23356"}],"version-history":[{"count":1,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/23356\/revisions"}],"predecessor-version":[{"id":23357,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/23356\/revisions\/23357"}],"wp:attachment":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/media?parent=23356"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/categories?post=23356"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/tags?post=23356"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}