{"id":16979,"date":"2026-09-21T05:44:00","date_gmt":"2026-09-21T05:44:00","guid":{"rendered":"https:\/\/www.examlabs.com\/certification\/?p=16979"},"modified":"2026-09-21T05:44:00","modified_gmt":"2026-09-21T05:44:00","slug":"microsoft-dp-600-practice-test-questions-and-exam-dumps-part20-q381-400","status":"publish","type":"post","link":"https:\/\/www.examlabs.com\/certification\/microsoft-dp-600-practice-test-questions-and-exam-dumps-part20-q381-400\/","title":{"rendered":"Microsoft DP-600 Practice Test Questions and Exam Dumps Part20 Q381-400"},"content":{"rendered":"

View Full <\/b>Microsoft DP-600 Exam Dumps<\/b><\/a> and Practice Test Dumps.<\/b><\/h2>\n

 <\/p>\n

Question 381<\/b><\/h3>\n

Which DAX function can rank a value against other values in a specified table or column?<\/b><\/p>\n

    \n
  1. RANKX<\/span><\/li>\n
  2. RANK<\/span><\/li>\n
  3. ORDERBY<\/span><\/li>\n
  4. SORT<\/span><\/li>\n<\/ol>\n

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

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

    RANKX evaluates an expression over a table and returns the rank of a value within that set. It is commonly used for analytical scenarios such as ranking products by revenue, customers by sales, or regions by performance. The function can evaluate expressions dynamically according to the current filter context, making it useful in semantic-model measures. The other listed functions are not equivalent DAX ranking functions. Therefore, RANKX is the appropriate choice when an analytical measure needs to determine the relative position of a value among other values.<\/span><\/p>\n

    Question 382<\/b><\/h3>\n

    Which Fabric feature allows an existing external storage location to be referenced from OneLake without physically copying all of its data into the lakehouse?<\/b><\/p>\n

      \n
    1. Dataflow Gen2<\/span><\/li>\n
    2. OneLake shortcut<\/span><\/li>\n
    3. Warehouse view<\/span><\/li>\n
    4. Semantic model<\/span><\/li>\n<\/ol>\n

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

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

      A OneLake shortcut provides a reference to data stored in another supported location, allowing Fabric workloads to access that data without creating a separate physical copy in OneLake. This can help reduce unnecessary data duplication and provide a unified data-access experience. Dataflow Gen2 is used for transformation and loading, Warehouse views expose queryable relational logic, and semantic models provide analytical structures. Therefore, a OneLake shortcut is the appropriate feature when data should be referenced from another storage location rather than copied into the lakehouse.<\/span><\/p>\n

      Question 383<\/b><\/h3>\n

      Which DAX function evaluates an expression under modified filter conditions and returns a scalar result?<\/b><\/p>\n

        \n
      1. CALCULATETABLE<\/span><\/li>\n
      2. FILTER<\/span><\/li>\n
      3. CALCULATE<\/span><\/li>\n
      4. ADDCOLUMNS<\/span><\/li>\n<\/ol>\n

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

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

        CALCULATE evaluates a scalar expression after modifying the current filter context. It is one of the most important DAX functions for creating measures that respond differently to filters, such as calculating sales for a specific category or ignoring a particular filter. CALCULATETABLE performs similar filter-context modification but returns a table expression. FILTER returns a filtered table, while ADDCOLUMNS adds calculated columns to a table expression. Therefore, CALCULATE is the appropriate function when a scalar calculation needs to be evaluated under changed filter conditions.<\/span><\/p>\n

        Question 384<\/b><\/h3>\n

        A Power Query query is used as a staging query for several downstream queries. Which approach helps avoid duplicating the same transformation logic?<\/b><\/p>\n

          \n
        1. Reference the staging query<\/span><\/li>\n
        2. Create a separate source connection for every query<\/span><\/li>\n
        3. Re-enter all transformation steps manually<\/span><\/li>\n
        4. Export each query as a separate semantic model<\/span><\/li>\n<\/ol>\n

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

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

          Referencing a staging query allows downstream queries to build on an existing query rather than duplicating its source connection and transformation steps. This approach can make Power Query solutions easier to maintain because common preparation logic is centralized. If the staging transformation changes, dependent queries can benefit from the updated logic without requiring the same steps to be recreated manually. Creating separate connections or duplicating transformation steps can increase maintenance overhead. Therefore, referencing a staging query is the appropriate approach for reusable transformation logic.<\/span><\/p>\n

          Question 385<\/b><\/h3>\n

          Which DAX function can return all selected values while respecting filters that remain outside the current visual context?<\/b><\/p>\n

            \n
          1. ALLSELECTED<\/span><\/li>\n
          2. REMOVEFILTERS<\/span><\/li>\n
          3. ALL<\/span><\/li>\n
          4. VALUES<\/span><\/li>\n<\/ol>\n

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

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

            ALLSELECTED returns a table or column that reflects the broader selection context while removing filters introduced by the current visual context. It is particularly useful for calculations such as percentages of a selected total, where the calculation should respect report-level or slicer selections but ignore certain visual-level grouping effects. ALL and REMOVEFILTERS can remove filters more broadly, while VALUES returns distinct values within the current context. Therefore, ALLSELECTED is the appropriate function when a calculation needs to respect the user’s broader selections.<\/span><\/p>\n

            Question 386<\/b><\/h3>\n

            Which Fabric workspace role generally provides the highest level of control over workspace content and settings?<\/b><\/p>\n

              \n
            1. Viewer<\/span><\/li>\n
            2. Contributor<\/span><\/li>\n
            3. Member<\/span><\/li>\n
            4. Admin<\/span><\/li>\n<\/ol>\n

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

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

              The Admin workspace role provides the broadest level of control among the standard Fabric workspace roles. An Admin can manage workspace settings and membership in addition to performing actions available to lower-level roles. Viewer primarily provides consumption access, while Contributor and Member provide progressively broader content-management capabilities without the complete administrative control of the Admin role. Workspace roles should be assigned according to the responsibilities of each user. Therefore, Admin is the role intended for users who require the highest level of workspace management authority.<\/span><\/p>\n

              Question 387<\/b><\/h3>\n

              Which DAX technique allows multiple expressions to be evaluated once and then reused within a measure?<\/b><\/p>\n

                \n
              1. Variables<\/span><\/li>\n
              2. Relationships<\/span><\/li>\n
              3. Perspectives<\/span><\/li>\n
              4. Display folders<\/span><\/li>\n<\/ol>\n

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

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

                DAX variables allow a measure to store the result of an expression under a named identifier and reuse that result later in the same calculation. Variables can make complex measures easier to read and maintain and may avoid repeatedly evaluating the same expression. They are particularly useful when a calculation contains several related steps or conditions. Relationships define connections between tables, perspectives organize model views, and display folders organize fields. Therefore, variables are the appropriate DAX technique for reusing intermediate expressions within a measure.<\/span><\/p>\n

                Question 388<\/b><\/h3>\n

                Which Fabric capability is designed to ingest and process event data in real time before it is consumed by downstream analytics?<\/b><\/p>\n

                  \n
                1. Eventstream<\/span><\/li>\n
                2. Warehouse<\/span><\/li>\n
                3. Perspective<\/span><\/li>\n
                4. Data category<\/span><\/li>\n<\/ol>\n

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

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

                  Eventstream is designed for real-time event ingestion and processing within Microsoft Fabric. It can connect to supported event sources, apply transformations or filtering, and route event data to destinations for further analysis. This makes it suitable for scenarios involving telemetry, application events, operational monitoring, and other continuously arriving data. Warehouse is intended for relational analytics, while perspectives and data categories are semantic-model features. Therefore, Eventstream is the appropriate Fabric capability when continuously arriving event data needs to be processed before downstream analytical use.<\/span><\/p>\n

                  Question 389<\/b><\/h3>\n

                  Which DAX function returns the number of rows in a table expression?<\/b><\/p>\n

                    \n
                  1. COUNT<\/span><\/li>\n
                  2. COUNTROWS<\/span><\/li>\n
                  3. DISTINCTCOUNT<\/span><\/li>\n
                  4. COUNTA<\/span><\/li>\n<\/ol>\n

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

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

                    COUNTROWS returns the number of rows in a table or table expression. It is useful when the calculation needs to count records rather than count values within a particular column. For example, COUNTROWS can count transactions returned by a FILTER expression. COUNT counts numeric values in a column, while DISTINCTCOUNT counts unique values and COUNTA counts nonblank values in a column. Therefore, COUNTROWS is the appropriate DAX function when the objective is to determine how many rows are present in a table expression.<\/span><\/p>\n

                    Question 390<\/b><\/h3>\n

                    Which Power Query operation combines columns from two queries by matching values in one or more key columns?<\/b><\/p>\n

                      \n
                    1. Append Queries<\/span><\/li>\n
                    2. Merge Queries<\/span><\/li>\n
                    3. Group By<\/span><\/li>\n
                    4. Unpivot Columns<\/span><\/li>\n<\/ol>\n

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

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

                      Merge Queries combines information from two queries by matching values in one or more selected columns. It is conceptually similar to joining tables and is useful when attributes from a related dataset need to be added to another query. Append Queries instead stacks rows from compatible datasets. Group By creates aggregations, while Unpivot Columns restructures columns into rows. Therefore, Merge Queries is the appropriate Power Query operation when columns from related datasets need to be combined using matching key values.<\/span><\/p>\n

                      Question 391<\/b><\/h3>\n

                      Which DAX function can return the earliest date from a column of dates?<\/b><\/p>\n

                        \n
                      1. MAX<\/span><\/li>\n
                      2. FIRSTNONBLANK<\/span><\/li>\n
                      3. MIN<\/span><\/li>\n
                      4. DATE<\/span><\/li>\n<\/ol>\n

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

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

                        MIN returns the smallest value in a column or expression, and for a date column this corresponds to the earliest date. It can be used to determine the first date represented in a dataset, such as the earliest transaction date or the beginning of an available reporting period. MAX returns the latest date, FIRSTNONBLANK has different behavior based on expression and context, and DATE constructs a date from year, month, and day values. Therefore, MIN is the appropriate function for identifying the earliest date.<\/span><\/p>\n

                        Question 392<\/b><\/h3>\n

                        Which semantic-model feature can control the sort order of one column based on the values of another column?<\/b><\/p>\n

                          \n
                        1. Data category<\/span><\/li>\n
                        2. Sort by Column<\/span><\/li>\n
                        3. Perspective<\/span><\/li>\n
                        4. Hierarchy<\/span><\/li>\n<\/ol>\n

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

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

                          Sort by Column allows one column to determine the ordering of another column. This is particularly useful for fields whose natural alphabetical order does not match their desired business order. For example, month names can be sorted using a numeric month-number column so that January appears before February and the remaining months follow chronological order. Data categories provide semantic classifications, perspectives customize model views, and hierarchies organize related fields. Therefore, Sort by Column is the appropriate feature for controlling custom column ordering.<\/span><\/p>\n

                          Question 393<\/b><\/h3>\n

                          Which KQL operator groups records and calculates aggregations such as counts or sums?<\/b><\/p>\n

                            \n
                          1. summarize<\/span><\/li>\n
                          2. project<\/span><\/li>\n
                          3. extend<\/span><\/li>\n
                          4. where<\/span><\/li>\n<\/ol>\n

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

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

                            The KQL summarize operator groups records and calculates aggregate results such as count, sum, average, minimum, or maximum. It is commonly used to produce analytical summaries from event data, such as counting errors by application or calculating total events by region. The project operator controls returned columns, extend creates calculated columns, and where filters records. Therefore, summarize is the appropriate KQL operator when grouped aggregation is required. It is especially useful for converting detailed event records into concise analytical results.<\/span><\/p>\n

                            Question 394<\/b><\/h3>\n

                            Which semantic-model security feature can restrict access to specific tables or columns rather than individual rows?<\/b><\/p>\n

                              \n
                            1. Row-level security<\/span><\/li>\n
                            2. Object-level security<\/span><\/li>\n
                            3. Workspace viewer access<\/span><\/li>\n
                            4. Sensitivity label<\/span><\/li>\n<\/ol>\n

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

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

                              Object-level security controls access to model objects such as tables and columns. It can be used when certain users should not be able to view particular model structures or fields at all. Row-level security addresses a different requirement by filtering the rows that users can see while generally allowing access to the same model objects. Workspace permissions control access to Fabric items, while sensitivity labels classify and protect information. Therefore, Object-level security is the appropriate feature when access must be restricted at the table or column level.<\/span><\/p>\n

                              Question 395<\/b><\/h3>\n

                              Which DAX function can return a table containing unique values from a column while removing duplicates?<\/b><\/p>\n

                                \n
                              1. VALUES<\/span><\/li>\n
                              2. DISTINCT<\/span><\/li>\n
                              3. COUNTROWS<\/span><\/li>\n
                              4. SUMMARIZECOLUMNS<\/span><\/li>\n<\/ol>\n

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

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

                                DISTINCT returns the unique values from a column or the distinct rows of a table expression, removing duplicate values from the result. It is useful when a calculation needs to operate on a set of unique values rather than every occurrence. VALUES can also return distinct values but can have different behavior concerning the blank row associated with relationships. COUNTROWS returns a scalar count, while SUMMARIZECOLUMNS is designed for grouped table results. Therefore, DISTINCT is the direct function when the requirement is to obtain unique values without duplicates.<\/span><\/p>\n

                                Question 396<\/b><\/h3>\n

                                Which Fabric capability can provide a graphical representation of how data moves from source assets through transformations to downstream analytical items?<\/b><\/p>\n

                                  \n
                                1. Lineage view<\/span><\/li>\n
                                2. Data category<\/span><\/li>\n
                                3. Display folder<\/span><\/li>\n
                                4. Slicer<\/span><\/li>\n<\/ol>\n

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

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

                                  Lineage view provides a visual representation of relationships and dependencies among supported Fabric items. It can help developers and administrators understand how upstream data sources, transformation processes, semantic models, reports, and other assets are connected. This is useful when assessing the impact of changes, tracing dependencies, or troubleshooting data solutions. Data categories and display folders organize semantic-model metadata, while slicers filter report data. Therefore, Lineage view is the appropriate capability for visually examining relationships across a data and analytics solution.<\/span><\/p>\n

                                  Question 397<\/b><\/h3>\n

                                  Which DAX function can activate an inactive relationship for the duration of a calculation?<\/b><\/p>\n

                                    \n
                                  1. CROSSFILTER<\/span><\/li>\n
                                  2. USERELATIONSHIP<\/span><\/li>\n
                                  3. RELATED<\/span><\/li>\n
                                  4. LOOKUPVALUE<\/span><\/li>\n<\/ol>\n

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

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

                                    USERELATIONSHIP enables an existing inactive relationship to participate in a calculation when used within an appropriate filter-context function such as CALCULATE. This is useful when a model contains multiple valid relationships between the same tables, such as separate Order Date and Ship Date relationships. One relationship can remain active for general reporting while another is activated only for specific measures. RELATED retrieves values through an active relationship, while the other functions serve different relationship or lookup purposes. Therefore, USERELATIONSHIP is appropriate for activating an inactive relationship during a calculation.<\/span><\/p>\n

                                    Question 398<\/b><\/h3>\n

                                    Which Fabric approach is most appropriate when a developer needs to execute custom Spark-based transformations that are difficult to express using low-code data preparation tools?<\/b><\/p>\n

                                      \n
                                    1. Notebook<\/span><\/li>\n
                                    2. Perspective<\/span><\/li>\n
                                    3. Warehouse view<\/span><\/li>\n
                                    4. Sensitivity label<\/span><\/li>\n<\/ol>\n

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

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

                                      A Fabric Notebook provides a code-based environment suitable for custom Spark processing and complex data-engineering transformations. It is useful when transformations require programmatic logic, custom libraries, iterative processing, or operations that are not conveniently represented through low-code interfaces. Perspectives and sensitivity labels serve semantic or governance purposes, while Warehouse views provide reusable SQL query logic. Therefore, a Notebook is the appropriate choice when custom Spark-based processing is required and the transformation cannot be efficiently implemented through simpler data-preparation tools.<\/span><\/p>\n

                                      Question 399<\/b><\/h3>\n

                                      Which DAX function can return a specified number of top rows from a table according to an expression used for ordering?<\/b><\/p>\n

                                        \n
                                      1. TOPN<\/span><\/li>\n
                                      2. RANKX<\/span><\/li>\n
                                      3. FILTER<\/span><\/li>\n
                                      4. VALUES<\/span><\/li>\n<\/ol>\n

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

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

                                        TOPN returns the top N rows of a table according to an expression used to determine the ordering. It is useful for scenarios such as identifying the ten products with the highest sales or the five customers with the greatest revenue. RANKX assigns rankings but does not directly return a top-N table in the same way. FILTER applies conditions, while VALUES returns distinct values. Therefore, TOPN is the appropriate DAX function when a table containing the highest-performing N records is required.<\/span><\/p>\n

                                        Question 400<\/b><\/h3>\n

                                        Which Fabric component is intended to provide a reusable analytical layer containing measures, relationships, and business-friendly fields for reporting?<\/b><\/p>\n

                                          \n
                                        1. Eventstream<\/span><\/li>\n
                                        2. Dataflow Gen2<\/span><\/li>\n
                                        3. Semantic model<\/span><\/li>\n
                                        4. OneLake shortcut<\/span><\/li>\n<\/ol>\n

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

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

                                          A semantic model provides the analytical layer used by reports and other consuming experiences. It can contain relationships, measures, calculated columns, hierarchies, perspectives, and business-friendly field definitions that help users analyze data consistently. Eventstream handles real-time event processing, Dataflow Gen2 focuses on data transformation and loading, and OneLake shortcuts provide references to external data locations. Therefore, a semantic model is the appropriate Fabric component for creating a reusable business-oriented analytical layer for reporting.<\/span><\/p>\n

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

                                          View Full Microsoft DP-600 Exam Dumps and Practice Test Dumps.   Question 381 Which DAX function can rank a value against other values in a specified table or column? RANKX RANK ORDERBY SORT Correct Answer: 1 Explanation RANKX evaluates an expression over a table and returns the rank of a value within that set. It […]<\/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\/16979"}],"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=16979"}],"version-history":[{"count":1,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/16979\/revisions"}],"predecessor-version":[{"id":16980,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/16979\/revisions\/16980"}],"wp:attachment":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/media?parent=16979"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/categories?post=16979"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/tags?post=16979"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}