{"id":23346,"date":"2026-09-28T05:09:42","date_gmt":"2026-09-28T05:09:42","guid":{"rendered":"https:\/\/www.examlabs.com\/certification\/?p=23346"},"modified":"2026-09-28T05:09:42","modified_gmt":"2026-09-28T05:09:42","slug":"tableau-tda-c01-practice-test-questions-and-exam-dumps-part14-q261-280","status":"publish","type":"post","link":"https:\/\/www.examlabs.com\/certification\/tableau-tda-c01-practice-test-questions-and-exam-dumps-part14-q261-280\/","title":{"rendered":"Tableau TDA-C01 Practice Test Questions and Exam Dumps Part14 Q261-280"},"content":{"rendered":"

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

 <\/p>\n

Question 261.<\/b><\/p>\n

An analyst wants to show the average Sales per Customer for each Region, even though Customer is not displayed in the view. Which Tableau calculation is most appropriate?<\/b><\/p>\n

    \n
  1. <\/b> { INCLUDE [Customer ID] : SUM([Sales]) }<\/span> used within an appropriate aggregation<\/span>
    \n<\/span>2.<\/b> RUNNING_SUM(SUM([Sales]))<\/span>
    \n<\/span>3.<\/b> { EXCLUDE [Region] : SUM([Sales]) }<\/span>
    \n<\/span>4.<\/b> INDEX()<\/span><\/li>\n<\/ol>\n

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

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

    An INCLUDE level-of-detail expression adds a dimension to the calculation grain even when that dimension is not visible in the worksheet. By including Customer ID, Tableau can first calculate Sales at the customer level and then aggregate those customer-level results at Region. This is useful for metrics such as average customer sales because simply applying AVG to row-level Sales may not represent the average customer total. Running Total and INDEX are table calculations based on marks already displayed. EXCLUDE removes dimensions rather than adding finer detail. INCLUDE is therefore the appropriate LOD pattern when a hidden dimension must participate in an intermediate calculation.<\/span><\/p>\n

    Question 262.<\/b><\/p>\n

    A worksheet displays Category and Sub-Category. The analyst wants a calculated value that shows Category-level Sales for every Sub-Category mark. Which LOD expression type should be used?<\/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: 2<\/b><\/p>\n

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

      An EXCLUDE LOD expression removes a dimension that is currently part of the visualization’s level of detail. If Category and Sub-Category are both displayed, excluding Sub-Category allows Tableau to calculate Sales at the Category level while still displaying the individual Sub-Category marks. This is useful for comparing each detailed member with its broader parent total. INCLUDE would add more detail, not remove it. Running Total and Rank are table calculations whose results depend on the displayed marks and addressing configuration. EXCLUDE directly expresses the requirement that one visible dimension should not participate in a particular calculation.<\/span><\/p>\n

      Question 263.<\/b><\/p>\n

      Which Tableau LOD expression is most appropriate when total Sales must always be calculated by Customer ID regardless of dimensions such as Region or Category added to the view?<\/b><\/p>\n

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

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

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

        A FIXED LOD expression calculates the measure at the explicitly stated dimensions, which in this case is Customer ID. <\/span>{ FIXED [Customer ID] : SUM([Sales]) }<\/span> therefore establishes customer-level sales independent of most dimensions added to the worksheet. Tableau’s order of operations still matters because context filters and some earlier filters can affect the data available to the FIXED calculation. INCLUDE works relative to the view’s current level of detail, while EXCLUDE removes specified dimensions from that level. WINDOW_SUM is a table calculation. FIXED is appropriate when the desired calculation grain should remain consistently defined.<\/span><\/p>\n

        Question 264.<\/b><\/p>\n

        Which Tableau table calculation is best for displaying the cumulative value of Profit across months?<\/b><\/p>\n

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

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

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

          Running Total accumulates an aggregated measure as Tableau moves across the specified addressing dimension. If Month is arranged chronologically, applying Running Total to SUM(Profit) produces cumulative Profit through each month. This can support year-to-date profitability analysis and progress monitoring. The Compute Using setting is important because it determines the direction in which the accumulation occurs and where it resets. Percent of Total calculates relative contribution, Rank assigns ordering, and Difference compares marks rather than accumulating them. Running Total is therefore the appropriate quick table calculation for cumulative monthly values.<\/span><\/p>\n

          Question 265.<\/b><\/p>\n

          Which Tableau table calculation should an analyst use to show each month’s Sales as a percentage of total annual Sales?<\/b><\/p>\n

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

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

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

            Percent of Total divides each mark’s aggregated value by the total value in the current table-calculation partition. If the partition represents one year and Month is the addressing dimension, Tableau can show each month’s share of annual Sales. The analyst should verify the Compute Using and partition settings so that the denominator resets for each year if multiple years are shown. Running Total accumulates values over time, Difference compares marks, and Moving Average smooths values over a window. Percent of Total is the most direct approach when the analytical question focuses on contribution to a whole.<\/span><\/p>\n

            Question 266.<\/b><\/p>\n

            Which Tableau function can retrieve the Sales value from two marks before the current mark within a table calculation?<\/b><\/p>\n

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

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

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

              LOOKUP()<\/span> returns an expression’s value from a relative position in the current table-calculation partition. An offset of <\/span>-2<\/span> retrieves the value from two marks before the current mark, assuming the view is ordered and addressed correctly. This can be useful for comparing current Sales with a value from two months earlier or for creating custom period-lag calculations. INDEX returns the sequential position of the current mark, SIZE returns the number of marks in the partition, and RANK assigns a value-based ordering. LOOKUP is specifically designed to reference values from neighboring or nearby marks.<\/span><\/p>\n

              Question 267.<\/b><\/p>\n

              An analyst wants to calculate the average of SUM(Sales) across a three-month rolling window. Which feature is most appropriate?<\/b><\/p>\n

                \n
              1. <\/b> Context filter<\/span>
                \n<\/span>2.<\/b> FIXED LOD expression<\/span>
                \n<\/span>3.<\/b> Moving Average table calculation<\/span>
                \n<\/span>4.<\/b> Geographic role<\/span><\/li>\n<\/ol>\n

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

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

                A Moving Average table calculation calculates an average across a specified window of marks. For monthly Sales, the analyst can configure the window so that each value reflects the current month and selected preceding months. This smooths short-term volatility and makes longer-term patterns easier to identify. Because it is a table calculation, the result depends on the view’s ordering, addressing, and partitioning. A context filter changes filter evaluation order, while FIXED LOD expressions control aggregation granularity rather than rolling windows. Geographic roles apply to mapping. Moving Average is therefore the most appropriate Tableau feature for a rolling mean across months.<\/span><\/p>\n

                Question 268.<\/b><\/p>\n

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

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

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

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

                  SIZE()<\/span> returns the number of marks or rows in the current table-calculation partition. This can be useful for calculations that depend on how many marks exist, such as conditional logic, custom pagination, or determining whether sufficient data is available for a rolling calculation. Like other table calculations, SIZE depends on the partitioning defined by the worksheet. INDEX returns a mark’s sequential position, LOOKUP retrieves another mark’s value using a relative offset, and FIRST returns the offset from the current row to the first row in the partition. SIZE specifically answers how many marks belong to the active partition.<\/span><\/p>\n

                  Question 269.<\/b><\/p>\n

                  A source system stores Product Code as <\/b>ABC-12345<\/b>, and the analyst wants to extract only <\/b>ABC<\/b>. Which Tableau function is most appropriate?<\/b><\/p>\n

                    \n
                  1. <\/b> LEFT([Product Code],3)<\/span>
                    \n<\/span>2.<\/b> RIGHT([Product Code],3)<\/span>
                    \n<\/span>3.<\/b> LEN([Product Code])<\/span>
                    \n<\/span>4.<\/b> UPPER([Product Code])<\/span><\/li>\n<\/ol>\n

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

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

                    The <\/span>LEFT()<\/span> function returns a specified number of characters from the beginning of a string. <\/span>LEFT([Product Code],3)<\/span> returns <\/span>ABC<\/span> from <\/span>ABC-12345<\/span>. This is useful when codes have consistent prefixes that represent product families, business units, territories, or other categories. RIGHT extracts characters from the end of the string, LEN returns its character count, and UPPER changes capitalization. LEFT is therefore the most direct function when the desired content occupies a known fixed-length prefix at the start of a text field.<\/span><\/p>\n

                    Question 270.<\/b><\/p>\n

                    Which Tableau function should an analyst use to determine whether Product Name contains the text <\/b>Desk<\/b> anywhere in the value?<\/b><\/p>\n

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

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

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

                      CONTAINS()<\/span> returns TRUE when the specified substring appears anywhere within a string. For example, <\/span>CONTAINS([Product Name],”Desk”)<\/span> identifies product names containing Desk regardless of whether it appears at the beginning, middle, or end. STARTSWITH and ENDSWITH test only the beginning or end of the string, while LEFT returns characters rather than a Boolean test. CONTAINS is useful for classifications, calculated filters, and text-based flags. Analysts may also need to normalize capitalization first if source values are inconsistent and the matching behavior needs to be standardized.<\/span><\/p>\n

                      Question 271.<\/b><\/p>\n

                      Which Tableau function can remove leading and trailing spaces from values such as <\/b>” East “<\/b> before they are grouped or compared?<\/b><\/p>\n

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

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

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

                        TRIM()<\/span> removes whitespace from both ends of a string. This is important because hidden spaces can cause values that look identical to be treated as separate members. For example, <\/span>“East”<\/span> and <\/span>“East “<\/span> may produce separate categories, fail to match cleanly, or behave unexpectedly in comparisons. REPLACE can substitute specified substrings, LOWER changes capitalization, and FIND returns the position of a substring. TRIM is a simple but effective data-cleaning function for text imported from spreadsheets, manually entered systems, and other sources where whitespace may not be consistently controlled.<\/span><\/p>\n

                        Question 272.<\/b><\/p>\n

                        Which Tableau string function should be used to replace <\/b>Corp.<\/b> with <\/b>Corporate<\/b> inside a text field?<\/b><\/p>\n

                          \n
                        1. <\/b> TRIM()<\/span>
                          \n<\/span>2.<\/b> LEFT()<\/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, <\/span>REPLACE([Segment],”Corp.”,”Corporate”)<\/span> can standardize an abbreviation for display or downstream calculations. This transformation occurs within Tableau and does not alter the original source field. TRIM removes surrounding spaces, LEFT extracts characters from the beginning, and FIND returns the position of a substring. REPLACE is particularly useful for normalizing known text patterns, correcting repeated abbreviations, or cleaning predictable source-system values when modifying the original data source is not practical.<\/span><\/p>\n

                          Question 273.<\/b><\/p>\n

                          Which Tableau function is most appropriate for calculating the number of days between a customer’s Signup Date and TODAY()?<\/b><\/p>\n

                            \n
                          1. <\/b> DATEDIFF(‘day’,[Signup Date],TODAY())<\/span>
                            \n<\/span>2.<\/b> DATEADD(‘day’,[Signup Date],TODAY())<\/span>
                            \n<\/span>3.<\/b> DATETRUNC(‘day’,[Signup Date])<\/span>
                            \n<\/span>4.<\/b> DAY(TODAY())-[Signup 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 using a specified unit. In this case, <\/span>DATEDIFF(‘day’,[Signup Date],TODAY())<\/span> determines the number of day boundaries between signup and the current date. This can be used for customer tenure, account age, ticket age, and similar elapsed-time metrics. DATEADD shifts a date rather than measuring elapsed time, while DATETRUNC rounds a date to a time boundary. Subtracting a date directly from the numeric day component is not an appropriate calculation. DATEDIFF is the standard Tableau function for measuring intervals between two dates.<\/span><\/p>\n

                            Question 274.<\/b><\/p>\n

                            Which Tableau function should an analyst use to move a date six months into the future?<\/b><\/p>\n

                              \n
                            1. <\/b> DATEDIFF()<\/span>
                              \n<\/span>2.<\/b> DATEADD(‘month’,6,[Date])<\/span>
                              \n<\/span>3.<\/b> MONTH()<\/span>
                              \n<\/span>4.<\/b> DATEPART()<\/span><\/li>\n<\/ol>\n

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

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

                              DATEADD()<\/span> creates a shifted date by adding or subtracting a specified number of date units. <\/span>DATEADD(‘month’,6,[Date])<\/span> moves the original date six months forward. Negative values can move dates backward. This function correctly handles changes across year boundaries and differing calendar months. DATEDIFF measures the distance between dates rather than shifting them, while MONTH and DATEPART extract components of a date. DATEADD is commonly used for renewal dates, expiration dates, projected milestones, comparison periods, and other calculations requiring a date offset.<\/span><\/p>\n

                              Question 275.<\/b><\/p>\n

                              Which Tableau function converts a date to the beginning of the month containing that date?<\/b><\/p>\n

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

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

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

                                DATETRUNC(‘month’,[Date])<\/span> returns the first day of the month containing the original date while preserving a date data type. This makes it useful for monthly grouping, relationships, custom calculations, and consistent period comparisons. MONTH extracts only the month number, while DATEPART can extract a requested date component. DATEDIFF calculates elapsed date units. DATETRUNC is particularly useful when analysts need all dates in the same month to map to one period-start date while still retaining the year and other date context.<\/span><\/p>\n

                                Question 276.<\/b><\/p>\n

                                Which Tableau function returns the current date and time?<\/b><\/p>\n

                                  \n
                                1. <\/b> TODAY()<\/span>
                                  \n<\/span>2.<\/b> DATE()<\/span>
                                  \n<\/span>3.<\/b> DATEPARSE()<\/span>
                                  \n<\/span>4.<\/b> NOW()<\/span><\/li>\n<\/ol>\n

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

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

                                  NOW()<\/span> returns the current date and time. It is useful when calculations require time-of-day precision, such as the number of hours since an event or whether a record is older than a particular number of minutes. <\/span>TODAY()<\/span> returns the current date without the same timestamp precision. DATE converts compatible values into a date, while DATEPARSE interprets text according to a specified date format where supported. Analysts should choose NOW when hours, minutes, or seconds matter and TODAY when the business calculation is based only on the current calendar date.<\/span><\/p>\n

                                  Question 277.<\/b><\/p>\n

                                  An analyst has separate tables for January, February, and March with the same columns. Which operation should be used to combine them into a single table containing all rows?<\/b><\/p>\n

                                    \n
                                  1. <\/b> Union<\/span>
                                    \n<\/span>2.<\/b> Join<\/span>
                                    \n<\/span>3.<\/b> Relationship<\/span>
                                    \n<\/span>4.<\/b> Set<\/span><\/li>\n<\/ol>\n

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

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

                                    A union combines rows vertically from tables with the same or compatible column structures. When January, February, and March tables contain the same fields, unioning them creates one dataset containing records from all three months. This is different from a join, which combines columns horizontally according to matching keys. Relationships preserve separate logical tables and determine how they interact based on the fields used in a view. Sets define dimension membership and do not combine source data. Union is therefore the correct operation when similarly structured tables represent different periods or partitions that need to be stacked together.<\/span><\/p>\n

                                    Question 278.<\/b><\/p>\n

                                    Which join type keeps only records that match the join condition in both physical tables?<\/b><\/p>\n

                                      \n
                                    1. <\/b> Left join<\/span>
                                      \n<\/span>2.<\/b> Inner join<\/span>
                                      \n<\/span>3.<\/b> Right join<\/span>
                                      \n<\/span>4.<\/b> Full outer join<\/span><\/li>\n<\/ol>\n

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

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

                                      An inner join returns rows only when the join keys match in both tables. Records that exist in only one table are excluded from the result. This is appropriate when the analysis should include only entities represented on both sides, but analysts should verify that valid records are not unintentionally lost because of incomplete or inconsistent join keys. A left join preserves all rows from the left table, a right join preserves all rows from the right, and a full outer join retains unmatched rows from both sides. Selecting the correct join type is important because it directly determines which records are available for downstream analysis.<\/span><\/p>\n

                                      Question 279.<\/b><\/p>\n

                                      An Orders table contains multiple rows per customer, and a Targets table contains one row per salesperson. The analyst wants to avoid unnecessarily duplicating target values through a physical join. Which Tableau modeling approach is often preferable?<\/b><\/p>\n

                                        \n
                                      1. <\/b> Union the tables<\/span>
                                        \n<\/span>2.<\/b> Convert Targets to a parameter<\/span>
                                        \n<\/span>3.<\/b> Use a relationship when the tables represent different grains and the model supports it<\/span>
                                        \n<\/span>4.<\/b> Create a bin from Target<\/span><\/li>\n<\/ol>\n

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

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

                                        Relationships allow logical tables to preserve their own levels of detail and let Tableau determine how to query them based on the fields used in a visualization. When Orders and Targets have different grains, a physical join may repeat target values across many order rows and can lead to incorrect aggregation if the repeated values are summed. A relationship can often avoid that premature row-level flattening. A union would stack rows rather than relate tables, while parameters and bins do not solve the data-modeling issue. Understanding the grain of each table is essential when deciding between relationships and physical joins.<\/span><\/p>\n

                                        Question 280.<\/b><\/p>\n

                                        A dashboard contains a map and three supporting charts. The analyst wants clicking a state on the map to restrict all three charts to that selected state. Which Tableau feature should be configured?<\/b><\/p>\n

                                          \n
                                        1. <\/b> Set action<\/span>
                                          \n<\/span>2.<\/b> Parameter action<\/span>
                                          \n<\/span>3.<\/b> Highlight 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 passes one or more selected values from a source worksheet to target worksheets and restricts the target data accordingly. The map can therefore act as an interactive filter: when a user selects a state, each supporting chart can be configured to display only records associated with that state. A highlight action would keep unrelated data visible while emphasizing matches. A parameter action updates a parameter, and a set action changes set membership. When the explicit goal is to remove unrelated records from multiple target views based on a user’s selection, a filter action is the most direct Tableau dashboard solution.<\/span><\/p>\n

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

                                          View Full Tableau TDA-C01 Exam Dumps and Practice Test Dumps   Question 261. An analyst wants to show the average Sales per Customer for each Region, even though Customer is not displayed in the view. Which Tableau calculation is most appropriate? { INCLUDE [Customer ID] : SUM([Sales]) } used within an appropriate aggregation 2. RUNNING_SUM(SUM([Sales])) […]<\/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\/23346"}],"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=23346"}],"version-history":[{"count":1,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/23346\/revisions"}],"predecessor-version":[{"id":23347,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/23346\/revisions\/23347"}],"wp:attachment":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/media?parent=23346"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/categories?post=23346"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/tags?post=23346"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}