{"id":16977,"date":"2026-09-21T05:43:38","date_gmt":"2026-09-21T05:43:38","guid":{"rendered":"https:\/\/www.examlabs.com\/certification\/?p=16977"},"modified":"2026-09-21T05:43:38","modified_gmt":"2026-09-21T05:43:38","slug":"microsoft-dp-600-practice-test-questions-and-exam-dumps-part19-q361-380","status":"publish","type":"post","link":"https:\/\/www.examlabs.com\/certification\/microsoft-dp-600-practice-test-questions-and-exam-dumps-part19-q361-380\/","title":{"rendered":"Microsoft DP-600 Practice Test Questions and Exam Dumps Part19 Q361-380"},"content":{"rendered":"

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

 <\/p>\n

Question 361<\/b><\/h3>\n

Which DAX function preserves existing filters on a column while adding a new filter condition?<\/b><\/p>\n

    \n
  1. KEEPFILTERS<\/span><\/li>\n
  2. ALL<\/span><\/li>\n
  3. REMOVEFILTERS<\/span><\/li>\n
  4. DISTINCT<\/span><\/li>\n<\/ol>\n

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

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

    KEEPFILTERS modifies how filters are applied within functions such as CALCULATE. Instead of replacing an existing filter on the same column or table, it preserves the existing filter context and intersects it with the new filter. This is useful when a calculation should become more restrictive without removing selections already applied by a report or visual. ALL and REMOVEFILTERS remove filters, while DISTINCT returns unique values. Therefore, KEEPFILTERS is the appropriate DAX function when existing filters need to remain active while an additional restriction is applied.<\/span><\/p>\n

    Question 362<\/b><\/h3>\n

    Which Fabric storage mode is designed to provide direct access to Delta tables in a lakehouse without requiring traditional import into the semantic model?<\/b><\/p>\n

      \n
    1. Import<\/span><\/li>\n
    2. DirectQuery<\/span><\/li>\n
    3. Direct Lake<\/span><\/li>\n
    4. Dual<\/span><\/li>\n<\/ol>\n

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

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

      Direct Lake is a semantic-model storage mode designed for working directly with Delta-formatted data stored in OneLake. Instead of following the traditional import process, the semantic model can access the lake data directly, helping provide low-latency analytical experiences while avoiding unnecessary duplication of the underlying data. Import mode loads data into the model, whereas DirectQuery sends queries to the source system. Dual is associated with composite modeling behavior. Therefore, Direct Lake is the storage mode specifically designed for direct analytical access to lakehouse Delta tables.<\/span><\/p>\n

      Question 363<\/b><\/h3>\n

      A report contains a measure that should return the currently selected product when exactly one product is selected. Which DAX function is suitable?<\/b><\/p>\n

        \n
      1. VALUES<\/span><\/li>\n
      2. SELECTEDVALUE<\/span><\/li>\n
      3. HASONEVALUE<\/span><\/li>\n
      4. DISTINCTCOUNT<\/span><\/li>\n<\/ol>\n

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

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

        SELECTEDVALUE returns the value of a column when the current context contains exactly one distinct value. It can also return an alternate result when zero or multiple values are present. This makes it particularly useful for dynamic titles, labels, and measures that need to display the currently selected product, region, or category. HASONEVALUE only tests whether one distinct value exists, while VALUES returns a table and DISTINCTCOUNT returns a count. Therefore, SELECTEDVALUE is the most direct choice for retrieving one selected product.<\/span><\/p>\n

        Question 364<\/b><\/h3>\n

        Which Fabric feature provides a centralized place to discover and explore data items available across an organization’s Fabric environment?<\/b><\/p>\n

          \n
        1. OneLake catalog<\/span><\/li>\n
        2. Power Query editor<\/span><\/li>\n
        3. DAX query view<\/span><\/li>\n
        4. Selection pane<\/span><\/li>\n<\/ol>\n

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

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

          OneLake catalog provides a centralized discovery experience for finding and exploring data and analytics items within Microsoft Fabric. It can help users locate relevant data assets, understand available content, and work with governed organizational data. Power Query editor is used for data transformation, DAX query view is focused on querying semantic models, and Selection pane manages report visual visibility and ordering. Therefore, OneLake catalog is the appropriate feature when the requirement is to discover and explore available Fabric data assets from a centralized location.<\/span><\/p>\n

          Question 365<\/b><\/h3>\n

          Which DAX function returns a table containing all rows from a specified table while removing filters from that table?<\/b><\/p>\n

            \n
          1. FILTER<\/span><\/li>\n
          2. ALL<\/span><\/li>\n
          3. VALUES<\/span><\/li>\n
          4. SELECTCOLUMNS<\/span><\/li>\n<\/ol>\n

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

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

            ALL can remove filters from a specified table or column and return the resulting table or column values. It is frequently used in DAX calculations that need to compare the current filtered result with an unrestricted total. For example, a percentage-of-total calculation can use ALL to remove a product filter from the denominator. FILTER applies conditions to create a subset, VALUES returns distinct values, and SELECTCOLUMNS creates a table containing selected or calculated columns. Therefore, ALL is appropriate when filters need to be removed from the specified table.<\/span><\/p>\n

            Question 366<\/b><\/h3>\n

            A semantic model contains two possible paths between tables, causing ambiguous filtering. Which modeling change can help resolve the ambiguity?<\/b><\/p>\n

              \n
            1. Add more bidirectional relationships<\/span><\/li>\n
            2. Remove or redesign the unnecessary relationship path<\/span><\/li>\n
            3. Convert every dimension into a fact table<\/span><\/li>\n
            4. Duplicate every measure<\/span><\/li>\n<\/ol>\n

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

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

              Ambiguous filter paths occur when multiple relationship routes can propagate filters between tables. This can produce unexpected results and make model behavior difficult to understand. A common solution is to remove an unnecessary relationship or redesign the model so that filtering follows a clear and intentional path. Adding more bidirectional relationships generally increases complexity rather than solving it. Converting dimensions into facts or duplicating measures does not address the underlying relationship ambiguity. Therefore, removing or redesigning the unnecessary relationship path is an appropriate modeling solution.<\/span><\/p>\n

              Question 367<\/b><\/h3>\n

              Which KQL operator creates a new calculated column without removing the existing columns from the result?<\/b><\/p>\n

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

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

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

                The KQL extend operator creates calculated columns and keeps the existing columns in the query result unless explicitly changed later. It is useful when additional values need to be derived from existing fields, such as calculating duration, categorizing events, or generating a transformed value. The project operator controls which columns are returned, where filters records, and summarize performs aggregation. Therefore, extend is the appropriate KQL operator when a calculated column should be added while retaining the existing fields.<\/span><\/p>\n

                Question 368<\/b><\/h3>\n

                Which Fabric capability allows a data engineer to copy data from a source system into a Fabric destination as part of an orchestrated workflow?<\/b><\/p>\n

                  \n
                1. Copy activity<\/span><\/li>\n
                2. Display folder<\/span><\/li>\n
                3. Perspective<\/span><\/li>\n
                4. Hierarchy<\/span><\/li>\n<\/ol>\n

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

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

                  Copy activity is used within Fabric data pipelines to move data from supported source systems to destination locations. It can be configured with connection information, source and destination settings, mappings, and other options required for data movement. Because it can be included as part of a pipeline, it also supports broader orchestration scenarios. Display folders, perspectives, and hierarchies are semantic-model organization features rather than data-movement mechanisms. Therefore, Copy activity is the appropriate capability when data needs to be transferred as part of a pipeline workflow.<\/span><\/p>\n

                  Question 369<\/b><\/h3>\n

                  Which DAX function evaluates an expression for each row of a table and returns the sum of the resulting values?<\/b><\/p>\n

                    \n
                  1. SUM<\/span><\/li>\n
                  2. SUMX<\/span><\/li>\n
                  3. COUNT<\/span><\/li>\n
                  4. MAXX<\/span><\/li>\n<\/ol>\n

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

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

                    SUMX is an iterator function that evaluates an expression separately for every row in a specified table and then adds the resulting values together. It is especially useful when the value to be aggregated is calculated rather than stored directly in a single column. For example, SUMX can calculate quantity multiplied by unit price for each sales row and then total those calculated amounts. SUM aggregates an existing column, COUNT counts values, and MAXX returns the largest calculated result. Therefore, SUMX is the appropriate function.<\/span><\/p>\n

                    Question 370<\/b><\/h3>\n

                    Which Fabric item is primarily intended for relational SQL analytics and can provide a SQL-based analytical endpoint for structured data?<\/b><\/p>\n

                      \n
                    1. Eventstream<\/span><\/li>\n
                    2. Warehouse<\/span><\/li>\n
                    3. Notebook<\/span><\/li>\n
                    4. Dataflow Gen2<\/span><\/li>\n<\/ol>\n

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

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

                      A Fabric Warehouse is designed for relational analytical workloads using SQL. It provides a structured environment for storing and querying analytical data and can support objects such as tables and views. This makes it appropriate for organizations that require SQL-based reporting, analytics, and data warehousing capabilities. Eventstream is focused on streaming data, Notebooks support code-based processing and analysis, and Dataflow Gen2 provides data transformation and integration. Therefore, Warehouse is the appropriate Fabric item when the primary requirement is relational SQL analytics.<\/span><\/p>\n

                      Question 371<\/b><\/h3>\n

                      Which DAX function can return an alternate expression when the first expression evaluates to BLANK?<\/b><\/p>\n

                        \n
                      1. COALESCE<\/span><\/li>\n
                      2. ISBLANK<\/span><\/li>\n
                      3. IF<\/span><\/li>\n
                      4. BLANK<\/span><\/li>\n<\/ol>\n

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

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

                        COALESCE evaluates multiple expressions and returns the first expression that is not BLANK. It is useful when a calculation should provide a fallback value if the preferred result is missing. For example, a measure can return an alternative metric or default value when its primary calculation produces BLANK. ISBLANK checks whether an expression is blank, while IF performs conditional logic and BLANK explicitly produces a blank result. Therefore, COALESCE is a convenient choice for handling blank results through fallback expressions.<\/span><\/p>\n

                        Question 372<\/b><\/h3>\n

                        Which Power Query operation combines rows from two queries that have compatible column structures?<\/b><\/p>\n

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

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

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

                          Append Queries combines rows from two or more queries into a single result. It is appropriate when datasets have compatible structures and represent similar types of records, such as monthly sales files that need to become one consolidated table. Merge Queries performs a join between queries based on matching columns, while Group By creates aggregations and Pivot Column reshapes data. Therefore, Append Queries is the appropriate operation when the objective is to stack compatible rows from multiple queries into one dataset.<\/span><\/p>\n

                          Question 373<\/b><\/h3>\n

                          Which DAX function can return a table with selected columns added as calculated expressions?<\/b><\/p>\n

                            \n
                          1. ADDCOLUMNS<\/span><\/li>\n
                          2. COUNTROWS<\/span><\/li>\n
                          3. CALCULATE<\/span><\/li>\n
                          4. DIVIDE<\/span><\/li>\n<\/ol>\n

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

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

                            ADDCOLUMNS returns a table with one or more calculated columns added to an existing table expression. Each added column is defined by an expression that is evaluated in the context of the current row. This makes ADDCOLUMNS useful for advanced DAX calculations where a temporary table needs additional calculated information. COUNTROWS returns a scalar row count, CALCULATE evaluates a scalar expression under modified filter context, and DIVIDE performs division. Therefore, ADDCOLUMNS is the appropriate function when calculated columns need to be added to a table expression.<\/span><\/p>\n

                            Question 374<\/b><\/h3>\n

                            A company wants to move a Fabric solution from a development workspace into a test workspace using a controlled promotion process. Which feature is designed for this purpose?<\/b><\/p>\n

                              \n
                            1. OneLake shortcut<\/span><\/li>\n
                            2. Deployment pipeline<\/span><\/li>\n
                            3. Eventstream<\/span><\/li>\n
                            4. Data category<\/span><\/li>\n<\/ol>\n

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

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

                              Deployment pipelines are designed to promote supported Fabric and Power BI content through development, test, and production stages. They help teams manage controlled movement of analytical items between environments and reduce the need to manually recreate content. OneLake shortcuts provide access to data stored elsewhere, Eventstream supports real-time data ingestion and processing, and data categories provide semantic metadata. Therefore, Deployment pipeline is the appropriate feature when a Fabric solution needs to move through controlled development and testing stages.<\/span><\/p>\n

                              Question 375<\/b><\/h3>\n

                              Which DAX function checks whether the current context contains exactly one distinct value for a column?<\/b><\/p>\n

                                \n
                              1. SELECTEDVALUE<\/span><\/li>\n
                              2. HASONEVALUE<\/span><\/li>\n
                              3. VALUES<\/span><\/li>\n
                              4. DISTINCTCOUNT<\/span><\/li>\n<\/ol>\n

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

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

                                HASONEVALUE returns TRUE when the current filter context contains exactly one distinct value for the specified column. It is commonly used when a measure should behave differently depending on whether the user has selected a single category, customer, or other dimension value. SELECTEDVALUE can retrieve that single value but is intended for returning the value itself. VALUES returns a table of values, while DISTINCTCOUNT returns the number of distinct values. Therefore, HASONEVALUE is the direct function for testing whether exactly one distinct value exists.<\/span><\/p>\n

                                Question 376<\/b><\/h3>\n

                                Which Power Query feature is useful for identifying the percentage of valid, error, and empty values in a column during data preparation?<\/b><\/p>\n

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

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

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

                                  Column quality provides a quick assessment of values within a Power Query column, including information about valid values, errors, and empty values. This is useful during data preparation because it can reveal quality problems before the data is loaded into a semantic model or other destination. Column distribution focuses on the frequency and distribution of values, while data category supplies semantic classification and Sort by Column controls ordering in a model. Therefore, Column quality is the appropriate feature for assessing valid, error, and empty values.<\/span><\/p>\n

                                  Question 377<\/b><\/h3>\n

                                  Which relationship design is commonly used when multiple fact records can correspond to one dimension record?<\/b><\/p>\n

                                    \n
                                  1. Many-to-many<\/span><\/li>\n
                                  2. One-to-one<\/span><\/li>\n
                                  3. Many-to-one<\/span><\/li>\n
                                  4. One-to-zero<\/span><\/li>\n<\/ol>\n

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

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

                                    A many-to-one relationship is commonly used between a fact table and a dimension table. Multiple fact rows, such as individual sales transactions, can reference the same dimension row, such as one product or customer. The dimension side contains unique keys, while the fact side can contain repeated foreign-key values. Many-to-many relationships are used for different modeling requirements and can introduce additional complexity. One-to-one relationships are less common in standard star schemas. Therefore, many-to-one is the typical relationship pattern between fact and dimension data.<\/span><\/p>\n

                                    Question 378<\/b><\/h3>\n

                                    Which KQL operator controls which columns are returned in the final query result?<\/b><\/p>\n

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

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

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

                                      The KQL project operator specifies which columns should appear in the query output and can also create renamed or calculated columns in the projection. It is useful for reducing unnecessary fields and presenting a focused result set. The where operator filters rows, extend adds calculated columns while retaining existing data, and count returns a row count. Therefore, project is the appropriate KQL operator when the objective is to control the columns included in the final query result.<\/span><\/p>\n

                                      Question 379<\/b><\/h3>\n

                                      Which semantic-model feature allows a report developer to expose different sets of fields for different analytical audiences without creating separate models?<\/b><\/p>\n

                                        \n
                                      1. Perspectives<\/span><\/li>\n
                                      2. Bookmarks<\/span><\/li>\n
                                      3. Slicers<\/span><\/li>\n
                                      4. Tooltips<\/span><\/li>\n<\/ol>\n

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

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

                                        Perspectives provide customized views of a semantic model by exposing selected tables, columns, and measures for particular analytical audiences. They can simplify the experience for users who do not need to see every object in a large model. A single underlying semantic model can therefore support different perspectives for different business groups. Bookmarks save report states, slicers filter report data, and tooltips provide contextual information when users interact with visuals. Therefore, Perspectives are appropriate when different audiences need simplified model views.<\/span><\/p>\n

                                        Question 380<\/b><\/h3>\n

                                        Which Fabric capability can create a reusable transformation process that can load data into supported destinations without requiring a full notebook-based solution?<\/b><\/p>\n

                                          \n
                                        1. Dataflow Gen2<\/span><\/li>\n
                                        2. Eventhouse<\/span><\/li>\n
                                        3. Semantic model<\/span><\/li>\n
                                        4. Report bookmark<\/span><\/li>\n<\/ol>\n

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

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

                                          Dataflow Gen2 provides a low-code data transformation experience based on Power Query and can be used to prepare and load data into supported Fabric destinations. It is useful when organizations need repeatable transformation logic without implementing the entire process through custom code in a notebook. Eventhouse is intended for real-time analytical workloads, semantic models provide analytical modeling, and bookmarks preserve report states. Therefore, Dataflow Gen2 is the appropriate capability for creating reusable, low-code data transformation and loading processes.<\/span><\/p>\n

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

                                          View Full Microsoft DP-600 Exam Dumps and Practice Test Dumps.   Question 361 Which DAX function preserves existing filters on a column while adding a new filter condition? KEEPFILTERS ALL REMOVEFILTERS DISTINCT Correct Answer: 1 Explanation KEEPFILTERS modifies how filters are applied within functions such as CALCULATE. Instead of replacing an existing filter on the […]<\/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\/16977"}],"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=16977"}],"version-history":[{"count":1,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/16977\/revisions"}],"predecessor-version":[{"id":16978,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/16977\/revisions\/16978"}],"wp:attachment":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/media?parent=16977"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/categories?post=16977"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/tags?post=16977"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}