{"id":16953,"date":"2026-09-21T05:33:00","date_gmt":"2026-09-21T05:33:00","guid":{"rendered":"https:\/\/www.examlabs.com\/certification\/?p=16953"},"modified":"2026-09-21T05:33:00","modified_gmt":"2026-09-21T05:33:00","slug":"microsoft-dp-600-practice-test-questions-and-exam-dumps-part9-q161-180","status":"publish","type":"post","link":"https:\/\/www.examlabs.com\/certification\/microsoft-dp-600-practice-test-questions-and-exam-dumps-part9-q161-180\/","title":{"rendered":"Microsoft DP-600 Practice Test Questions and Exam Dumps Part9 Q161-180"},"content":{"rendered":"

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

 <\/p>\n

Question 161<\/b><\/h3>\n

Which Microsoft Fabric capability allows users to analyze data with SQL without requiring them to work directly with Spark notebooks?<\/b><\/p>\n

    \n
  1. Eventstream<\/span><\/li>\n
  2. SQL analytics endpoint<\/span><\/li>\n
  3. Real-Time hub<\/span><\/li>\n
  4. Dataflow Gen2<\/span><\/li>\n<\/ol>\n

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

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

    The SQL analytics endpoint provides a SQL-based interface for querying supported lakehouse tables. It is useful for analysts and developers who prefer SQL rather than Spark-based development. The endpoint allows users to query structured data using familiar SQL syntax while the underlying lakehouse remains part of the broader Fabric environment. Eventstream and Real-Time hub focus on streaming scenarios, while Dataflow Gen2 is primarily used for data integration and transformation. Therefore, the SQL analytics endpoint is the appropriate choice for SQL-based analysis of lakehouse data.<\/span><\/p>\n

    Question 162<\/b><\/h3>\n

    Which DAX function returns the current filter context’s maximum value from an expression evaluated over a table?<\/b><\/p>\n

      \n
    1. MINX<\/span><\/li>\n
    2. COUNTX<\/span><\/li>\n
    3. MAXX<\/span><\/li>\n
    4. AVERAGEX<\/span><\/li>\n<\/ol>\n

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

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

      MAXX is an iterator function that evaluates an expression for each row of a table and returns the largest resulting value. It is useful when the maximum cannot be obtained simply by referencing an existing numeric column and instead requires a row-level calculation. MINX returns the smallest result, COUNTX counts expression results, and AVERAGEX calculates an average. Therefore, MAXX is appropriate when a DAX calculation needs to evaluate an expression across rows and then identify the highest resulting value.<\/span><\/p>\n

      Question 163<\/b><\/h3>\n

      A Power Query query needs to keep only rows where SalesAmount is greater than 10,000. Which operation should be applied?<\/b><\/p>\n

        \n
      1. Filter Rows<\/span><\/li>\n
      2. Pivot Column<\/span><\/li>\n
      3. Append Queries<\/span><\/li>\n
      4. Transpose<\/span><\/li>\n<\/ol>\n

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

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

        Filter Rows allows Power Query to retain records that meet a specified condition. In this scenario, a filter can be applied to SalesAmount so that only rows with values greater than 10,000 remain in the query result. This reduces unwanted data before it reaches downstream analytical models. Pivot Column changes the structure of data, Append Queries combines rows from multiple tables, and Transpose switches rows and columns. Therefore, Filter Rows is the correct operation for restricting records according to a numerical condition.<\/span><\/p>\n

        Question 164<\/b><\/h3>\n

        Which semantic-model feature allows a measure to use a predefined expression repeatedly without duplicating the calculation in multiple visuals?<\/b><\/p>\n

          \n
        1. Calculated table<\/span><\/li>\n
        2. Measure<\/span><\/li>\n
        3. Relationship<\/span><\/li>\n
        4. Hierarchy<\/span><\/li>\n<\/ol>\n

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

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

          A measure stores a reusable DAX calculation that can be referenced by multiple visuals and reports connected to the semantic model. Measures are evaluated dynamically according to the current filter and evaluation context, making them suitable for business metrics such as revenue, margin, or customer count. A calculated table creates a table expression, relationships connect model objects, and hierarchies organize fields for navigation. Therefore, a measure is the appropriate semantic-model feature when a calculation should be defined once and reused across multiple visuals.<\/span><\/p>\n

          Question 165<\/b><\/h3>\n

          Which Microsoft Fabric capability is intended to provide a centralized experience for discovering organizational data assets?<\/b><\/p>\n

            \n
          1. OneLake catalog<\/span><\/li>\n
          2. Deployment pipeline<\/span><\/li>\n
          3. Notebook<\/span><\/li>\n
          4. Eventstream<\/span><\/li>\n<\/ol>\n

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

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

            The OneLake catalog provides discovery capabilities for data and analytical assets within Microsoft Fabric. It helps users locate relevant organizational data and understand available resources rather than requiring them to search manually through numerous workspaces and items. Deployment pipelines support content lifecycle management, notebooks provide code-based development, and Eventstream focuses on real-time event processing. Therefore, the OneLake catalog is the appropriate capability when the primary requirement is discovering available organizational data assets.<\/span><\/p>\n

            Question 166<\/b><\/h3>\n

            Which DAX function can return the median value of a numeric column?<\/b><\/p>\n

              \n
            1. AVERAGE<\/span><\/li>\n
            2. MEDIAN<\/span><\/li>\n
            3. MAX<\/span><\/li>\n
            4. SUM<\/span><\/li>\n<\/ol>\n

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

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

              MEDIAN returns the middle value of a numeric dataset when the values are ordered. It can be useful for analytical scenarios where the average may be influenced by unusually high or low values. For example, median transaction value can provide a different perspective from average transaction value when transaction amounts vary significantly. AVERAGE calculates the arithmetic mean, MAX returns the largest value, and SUM calculates a total. Therefore, MEDIAN is the appropriate DAX function when the middle value of a numeric distribution is required.<\/span><\/p>\n

              Question 167<\/b><\/h3>\n

              A Fabric developer needs to move a table from a source system into a destination as part of a scheduled workflow. Which pipeline activity is most appropriate?<\/b><\/p>\n

                \n
              1. Wait<\/span><\/li>\n
              2. Copy data<\/span><\/li>\n
              3. For Each<\/span><\/li>\n
              4. Web<\/span><\/li>\n<\/ol>\n

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

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

                The Copy Data activity is designed to move data from supported source systems into supported destinations. It can be incorporated into a Fabric data pipeline and executed according to the pipeline’s scheduling and orchestration requirements. Activities such as Wait pause execution, For Each supports iterative processing, and Web can interact with web-based endpoints where supported. Therefore, Copy Data is the appropriate pipeline activity when the primary requirement is transferring a table from a source system to a destination.<\/span><\/p>\n

                Question 168<\/b><\/h3>\n

                Which Power BI capability allows a report page to contain a visual that displays detailed information based on the context passed from another page?<\/b><\/p>\n

                  \n
                1. Tooltip<\/span><\/li>\n
                2. Drillthrough<\/span><\/li>\n
                3. Slicer<\/span><\/li>\n
                4. Bookmark<\/span><\/li>\n<\/ol>\n

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

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

                  Drillthrough allows a report user to move from a summary visual to another page containing detailed information filtered by the selected context. A report can have a dedicated customer, product, or transaction detail page that receives the relevant filter when the user initiates drillthrough. A tooltip displays information when hovering, a slicer provides filtering controls, and a bookmark stores a predefined report state. Therefore, Drillthrough is the appropriate capability for navigating to a contextual detail page based on a selected data point.<\/span><\/p>\n

                  Question 169<\/b><\/h3>\n

                  Which DAX function can return a value from a related table when evaluated in an appropriate row context?<\/b><\/p>\n

                    \n
                  1. RELATED<\/span><\/li>\n
                  2. CALCULATE<\/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

                    RELATED retrieves a value from a related table when an appropriate relationship exists and the calculation is evaluated in a suitable row context. It is commonly used in calculated columns when an attribute from a related dimension needs to be brought into another table. CALCULATE modifies filter context, FILTER returns a filtered table expression, and VALUES returns distinct values from a column or table expression. Therefore, RELATED is the appropriate function for retrieving a corresponding value from a related table.<\/span><\/p>\n

                    Question 170<\/b><\/h3>\n

                    Which Microsoft Fabric item is most appropriate for storing raw files together with managed analytical tables?<\/b><\/p>\n

                      \n
                    1. Warehouse<\/span><\/li>\n
                    2. Lakehouse<\/span><\/li>\n
                    3. Eventhouse<\/span><\/li>\n
                    4. Semantic model<\/span><\/li>\n<\/ol>\n

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

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

                      A lakehouse combines data-lake storage with managed analytical tables and is designed to support both file-based and structured data workloads. Raw files can be stored alongside tables, allowing engineering and analytical workloads to work from a common Fabric data foundation. A Warehouse focuses on structured SQL analytics, Eventhouse targets real-time event data, and a semantic model provides the analytical layer used for reporting. Therefore, a lakehouse is the most appropriate Fabric item for storing raw files together with managed analytical tables.<\/span><\/p>\n

                      Question 171<\/b><\/h3>\n

                      Which DAX function can remove filters from a specific column while allowing filters on other columns to remain active?<\/b><\/p>\n

                        \n
                      1. ALLSELECTED<\/span><\/li>\n
                      2. REMOVEFILTERS<\/span><\/li>\n
                      3. FORMAT<\/span><\/li>\n
                      4. RELATED<\/span><\/li>\n<\/ol>\n

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

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

                        REMOVEFILTERS can remove filters from specified tables or columns when used within a DAX calculation. This allows developers to control which filters should be ignored while other parts of the current evaluation context remain active. It is frequently used with CALCULATE for calculations such as percentages of totals. ALLSELECTED has different behavior because it works with selections retained from the surrounding query context. FORMAT changes value representation and RELATED retrieves related values. Therefore, REMOVEFILTERS is the appropriate function for explicitly clearing filters from selected model objects.<\/span><\/p>\n

                        Question 172<\/b><\/h3>\n

                        A semantic model has a Sales fact table and a Product dimension. Which table should normally contain descriptive fields such as ProductName and ProductCategory?<\/b><\/p>\n

                          \n
                        1. Sales<\/span><\/li>\n
                        2. Product<\/span><\/li>\n
                        3. Date<\/span><\/li>\n
                        4. Measures table<\/span><\/li>\n<\/ol>\n

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

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

                          Descriptive attributes such as ProductName and ProductCategory normally belong in the Product dimension. The Sales fact table should primarily contain measurable business events and keys that connect those events to dimensions. Keeping descriptive information in dimensions supports a star-schema design and allows users to filter and group sales consistently by product attributes. The Date table is intended for calendar-related attributes, while a measures table is used for organizing calculations. Therefore, the Product dimension is the appropriate location for ProductName and ProductCategory.<\/span><\/p>\n

                          Question 173<\/b><\/h3>\n

                          Which Power Query transformation changes a column’s values from one data type to another, such as text to whole number?<\/b><\/p>\n

                            \n
                          1. Change Type<\/span><\/li>\n
                          2. Group By<\/span><\/li>\n
                          3. Merge Queries<\/span><\/li>\n
                          4. Fill Down<\/span><\/li>\n<\/ol>\n

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

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

                            Change Type modifies the data type assigned to a column in Power Query. Converting a text representation of a number into a whole-number or decimal type allows the value to participate correctly in numerical calculations and aggregations. Group By summarizes rows, Merge Queries combines related information from another table, and Fill Down propagates values into blank cells. Therefore, Change Type is the appropriate transformation when the underlying data needs to be interpreted using a different data type.<\/span><\/p>\n

                            Question 174<\/b><\/h3>\n

                            Which DAX function can calculate the number of distinct products sold under the current filter context?<\/b><\/p>\n

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

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

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

                              DISTINCTCOUNT returns the number of unique values in a specified column within the current evaluation context. If ProductID is placed in the function, the result represents the number of distinct products visible under the active report filters. COUNT counts qualifying values rather than necessarily unique values, COUNTROWS counts records, and SUMX performs row-by-row expression evaluation followed by summation. Therefore, DISTINCTCOUNT is the correct function for calculating the number of unique products represented in the current context.<\/span><\/p>\n

                              Question 175<\/b><\/h3>\n

                              Which Fabric lifecycle feature allows teams to compare supported content between development and production stages before deploying changes?<\/b><\/p>\n

                                \n
                              1. Real-Time hub<\/span><\/li>\n
                              2. Deployment pipelines<\/span><\/li>\n
                              3. OneLake shortcut<\/span><\/li>\n
                              4. Dataflow parameter<\/span><\/li>\n<\/ol>\n

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

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

                                Deployment pipelines support controlled movement of supported Fabric and Power BI content through lifecycle stages such as development, test, and production. Teams can review and compare changes between stages before promoting content, helping reduce the risk of publishing unfinished or unintended modifications. Real-Time hub supports discovery of event data, OneLake shortcuts reference external data, and dataflow parameters control configurable transformation values. Therefore, Deployment pipelines are the appropriate lifecycle feature for comparing and managing content across development and production stages.<\/span><\/p>\n

                                Question 176<\/b><\/h3>\n

                                Which Power BI feature can display additional report information when a user points to a data point without navigating to another page?<\/b><\/p>\n

                                  \n
                                1. Tooltip<\/span><\/li>\n
                                2. Drillthrough<\/span><\/li>\n
                                3. Bookmark<\/span><\/li>\n
                                4. Slicer<\/span><\/li>\n<\/ol>\n

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

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

                                  A tooltip displays additional information when a user hovers over a supported visual element. Report authors can configure tooltip content to provide supplementary measures, descriptions, or even dedicated tooltip pages without requiring the user to leave the current report page. Drillthrough navigates to another page, bookmarks save predefined report states, and slicers provide interactive filtering. Therefore, Tooltip is the appropriate Power BI feature when users need contextual information to appear during hover interactions without navigating away from the current page.<\/span><\/p>\n

                                  Question 177<\/b><\/h3>\n

                                  Which DAX function can evaluate an expression for each row of a table and return the smallest resulting value?<\/b><\/p>\n

                                    \n
                                  1. MIN<\/span><\/li>\n
                                  2. MINX<\/span><\/li>\n
                                  3. MAXX<\/span><\/li>\n
                                  4. SUMX<\/span><\/li>\n<\/ol>\n

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

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

                                    MINX is an iterator function that evaluates an expression for each row of a table and returns the smallest result produced by that expression. It is useful when the required minimum must first be calculated from row-level logic rather than directly taken from an existing column. MIN returns the minimum value from a column, MAXX finds the largest row-level expression result, and SUMX aggregates row-level expressions by addition. Therefore, MINX is appropriate when the minimum must be determined after evaluating an expression for each row.<\/span><\/p>\n

                                    Question 178<\/b><\/h3>\n

                                    Which modeling practice can help improve semantic-model performance by avoiding unnecessary high-cardinality columns?<\/b><\/p>\n

                                      \n
                                    1. Add more unique identifiers to every visual<\/span><\/li>\n
                                    2. Remove unused high-cardinality columns<\/span><\/li>\n
                                    3. Duplicate all dimension tables<\/span><\/li>\n
                                    4. Enable bidirectional filtering everywhere<\/span><\/li>\n<\/ol>\n

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

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

                                      Unused high-cardinality columns can consume significant storage and may reduce semantic-model efficiency. Removing columns that are not required for relationships, calculations, filtering, grouping, or reporting can reduce model size and improve processing characteristics. Adding unique identifiers unnecessarily increases cardinality, duplicated dimensions increase model complexity, and excessive bidirectional filtering can create ambiguous filter paths. Therefore, removing unused high-cardinality columns is a practical modeling optimization that can help improve semantic-model performance.<\/span><\/p>\n

                                      Question 179<\/b><\/h3>\n

                                      Which Microsoft Fabric feature is specifically intended for transforming data through a graphical, low-code Power Query interface?<\/b><\/p>\n

                                        \n
                                      1. Dataflow Gen2<\/span><\/li>\n
                                      2. Eventhouse<\/span><\/li>\n
                                      3. Warehouse<\/span><\/li>\n
                                      4. Deployment pipeline<\/span><\/li>\n<\/ol>\n

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

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

                                        Dataflow Gen2 provides a graphical, low-code data preparation experience based on Power Query. It allows users to connect to supported sources, clean and transform data, and write the resulting data to supported destinations. This makes it useful when transformation logic needs to be developed without relying entirely on code-based notebooks. Eventhouse is designed for real-time analytics, Warehouse provides structured SQL analytics, and deployment pipelines manage content lifecycle. Therefore, Dataflow Gen2 is the appropriate Fabric capability for low-code Power Query transformations.<\/span><\/p>\n

                                        Question 180<\/b><\/h3>\n

                                        Which DAX function can return a table containing the dates from the current period shifted to the previous year?<\/b><\/p>\n

                                          \n
                                        1. DATE<\/span><\/li>\n
                                        2. SAMEPERIODLASTYEAR<\/span><\/li>\n
                                        3. MONTH<\/span><\/li>\n
                                        4. FORMAT<\/span><\/li>\n<\/ol>\n

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

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

                                          SAMEPERIODLASTYEAR returns a table containing dates corresponding to the same period in the previous year based on the current date context. It is commonly used with CALCULATE to create year-over-year analytical measures. For example, a measure can compare current sales against sales for the equivalent period of the previous year. DATE creates date values, MONTH extracts a month number, and FORMAT changes value representation. Therefore, SAMEPERIODLASTYEAR is the appropriate DAX function for shifting the current date period back by one year.<\/span><\/p>\n

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

                                          View Full Microsoft DP-600 Exam Dumps and Practice Test Dumps.   Question 161 Which Microsoft Fabric capability allows users to analyze data with SQL without requiring them to work directly with Spark notebooks? Eventstream SQL analytics endpoint Real-Time hub Dataflow Gen2 Correct Answer: 2 Explanation The SQL analytics endpoint provides a SQL-based interface for querying […]<\/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\/16953"}],"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=16953"}],"version-history":[{"count":1,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/16953\/revisions"}],"predecessor-version":[{"id":16954,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/16953\/revisions\/16954"}],"wp:attachment":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/media?parent=16953"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/categories?post=16953"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/tags?post=16953"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}