{"id":15816,"date":"2026-09-18T09:42:20","date_gmt":"2026-09-18T09:42:20","guid":{"rendered":"https:\/\/www.examlabs.com\/certification\/?p=15816"},"modified":"2026-09-18T09:42:20","modified_gmt":"2026-09-18T09:42:20","slug":"microsoft-sc-200-practice-test-questions-and-exam-dumps-part19-q361-380","status":"publish","type":"post","link":"https:\/\/www.examlabs.com\/certification\/microsoft-sc-200-practice-test-questions-and-exam-dumps-part19-q361-380\/","title":{"rendered":"Microsoft SC-200 Practice Test Questions and Exam Dumps Part19 Q361-380"},"content":{"rendered":"

<\/h1>\n

View Full <\/b>Microsoft SC-200 Exam Dumps<\/b><\/a> and Practice Test Dumps.<\/b><\/h2>\n

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

Which Microsoft Sentinel component is responsible for collecting security data from external services and sources?<\/b><\/p>\n

    \n
  1. Workbook<\/span><\/li>\n
  2. Data connector<\/span><\/li>\n
  3. Automation rule<\/span><\/li>\n
  4. Watchlist<\/span><\/li>\n<\/ol>\n

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

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

    Microsoft Sentinel data connectors provide integrations that bring data from supported Microsoft services, third-party products, and other sources into the Sentinel environment. Once configured, connectors can make relevant security telemetry available for investigation, analytics rules, hunting, and visualization. The exact configuration depends on the source and connector type. Analysts should verify that the connector is enabled, receiving expected events, and configured with appropriate permissions. Missing or incomplete data collection can affect detection quality, so monitoring connector health is an important part of maintaining Sentinel visibility.<\/span><\/p>\n

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

    Which KQL operator can combine records from two datasets using a related field?<\/b><\/p>\n

      \n
    1. join<\/span><\/li>\n
    2. project<\/span><\/li>\n
    3. extend<\/span><\/li>\n
    4. order by<\/span><\/li>\n<\/ol>\n

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

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

      The KQL <\/span>join<\/span> operator combines rows from two tables or datasets based on related columns. This can be useful when analysts need to correlate information stored in separate telemetry sources. For example, authentication records can potentially be joined with another dataset containing user or device information. Analysts should select an appropriate join type and matching fields because an incorrect join can produce incomplete or unexpectedly large results. When investigating security activity, analysts should also consider timestamps and other contextual fields to ensure that the correlated records are genuinely related.<\/span><\/p>\n

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

      A security analyst wants to investigate a suspicious process and determine whether related activity occurred on other endpoints. Which capability is most appropriate?<\/b><\/p>\n

        \n
      1. Microsoft Defender Advanced Hunting<\/span><\/li>\n
      2. Microsoft Secure Score<\/span><\/li>\n
      3. Sentinel workbook<\/span><\/li>\n
      4. Attack simulation training<\/span><\/li>\n<\/ol>\n

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

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

        Microsoft Defender Advanced Hunting allows analysts to search endpoint and other security telemetry using KQL. An analyst can search for a suspicious process name, executable path, command line, hash, or related indicator and determine whether similar activity occurred across additional devices. This can help establish the scope of a potential compromise and identify related systems. Analysts should investigate surrounding events, timestamps, users, and network activity rather than relying only on a process name because legitimate software may use names or paths that resemble suspicious activity.<\/span><\/p>\n

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

        Which Microsoft Sentinel feature can execute a predefined workflow for actions such as sending notifications or enriching indicators?<\/b><\/p>\n

          \n
        1. Workbook<\/span><\/li>\n
        2. Watchlist<\/span><\/li>\n
        3. Playbook<\/span><\/li>\n
        4. Analytics rule<\/span><\/li>\n<\/ol>\n

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

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

          Microsoft Sentinel playbooks provide automated workflows built with Azure Logic Apps. They can perform actions such as sending notifications, enriching indicators, creating tickets, communicating with external services, or carrying out other supported response tasks. Playbooks can be triggered manually or through configured automation and incident workflows. This helps reduce repetitive analyst tasks and standardize responses. Administrators should carefully control permissions and test workflows before production deployment. A playbook should be designed with clear conditions and safeguards so automated actions do not unintentionally affect unrelated incidents or systems.<\/span><\/p>\n

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

          Which KQL function returns the largest value within a group?<\/b><\/p>\n

            \n
          1. max()<\/span><\/li>\n
          2. min()<\/span><\/li>\n
          3. avg()<\/span><\/li>\n
          4. dcount()<\/span><\/li>\n<\/ol>\n

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

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

            The KQL <\/span>max()<\/span> aggregation function returns the highest value within the selected dataset or group. It can be used with numeric fields as well as timestamp values. For example, an analyst can use <\/span>summarize max(Timestamp) by DeviceName<\/span> to identify the latest observed event for each device. This can help establish the most recent activity during an investigation. Analysts should ensure that the selected field is appropriate for the aggregation and that the dataset has been filtered to the intended investigation period before interpreting the result.<\/span><\/p>\n

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

            Which Microsoft Defender for Identity capability is particularly useful for detecting suspicious lateral movement involving identities?<\/b><\/p>\n

              \n
            1. Safe Links<\/span><\/li>\n
            2. Identity-based threat detection<\/span><\/li>\n
            3. Threat Explorer<\/span><\/li>\n
            4. Device discovery<\/span><\/li>\n<\/ol>\n

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

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

              Microsoft Defender for Identity provides identity-focused security monitoring that can help detect suspicious activities involving Active Directory identities. This includes behaviors associated with reconnaissance, credential attacks, privilege-related activity, and lateral movement. Identity-based detections can provide valuable context when an attacker attempts to move between systems using compromised credentials. Analysts should correlate Defender for Identity alerts with endpoint, authentication, and network telemetry to determine the broader attack sequence. Legitimate administrative operations can sometimes resemble malicious behavior, so analysts should validate the activity before taking containment or remediation actions.<\/span><\/p>\n

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

              Which KQL operator can rename or create a calculated field without aggregating the underlying records?<\/b><\/p>\n

                \n
              1. summarize<\/span><\/li>\n
              2. extend<\/span><\/li>\n
              3. distinct<\/span><\/li>\n
              4. join<\/span><\/li>\n<\/ol>\n

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

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

                The KQL <\/span>extend<\/span> operator adds calculated columns to the existing result set without grouping records into aggregates. Analysts can use it to derive categories, perform calculations, or create values based on existing fields. For example, an analyst could create a risk category from a numerical score and then filter the results using that new field. Unlike <\/span>summarize<\/span>, <\/span>extend<\/span> retains the individual records. Analysts should use descriptive column names and verify the calculation logic before using the resulting field in additional filters, visualizations, or investigation queries.<\/span><\/p>\n

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

                Which Microsoft Sentinel capability allows analysts to maintain reference values that can be used across multiple queries?<\/b><\/p>\n

                  \n
                1. Content hub<\/span><\/li>\n
                2. Workbook<\/span><\/li>\n
                3. Watchlist<\/span><\/li>\n
                4. Playbook<\/span><\/li>\n<\/ol>\n

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

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

                  Microsoft Sentinel watchlists store reference information that can be reused in queries and detection scenarios. Organizations can maintain lists of values such as trusted IP addresses, approved users, critical assets, or known indicators. Analysts can then reference the watchlist when investigating or filtering security events. This helps avoid repeatedly embedding the same reference data into individual queries. Watchlists must be maintained carefully because outdated entries can affect investigation results or detection logic. Analysts should document the purpose, ownership, and update process for important watchlists used by security operations.<\/span><\/p>\n

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

                  Which KQL operator should be used to select only specific columns from query results?<\/b><\/p>\n

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

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

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

                    The KQL <\/span>project<\/span> operator controls which columns appear in the query output. Analysts can use it to return only fields relevant to an investigation, such as username, device name, timestamp, and source IP address. This can make large result sets easier to read and can help focus analysis on important information. Unlike <\/span>where<\/span>, <\/span>project<\/span> does not filter rows based on a condition. Analysts should be careful not to remove fields required by later query operations, especially when constructing multi-stage KQL queries.<\/span><\/p>\n

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

                    Which Microsoft Defender XDR feature provides security information about important threats and their associated attack techniques?<\/b><\/p>\n

                      \n
                    1. Device discovery<\/span><\/li>\n
                    2. Threat analytics<\/span><\/li>\n
                    3. Live response<\/span><\/li>\n
                    4. Exposure management<\/span><\/li>\n<\/ol>\n

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

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

                      Microsoft Defender threat analytics provides security information about significant threats and can include details about threat behavior, techniques, affected products, indicators, and recommended protections. Analysts can use this information to understand known threats and compare documented behaviors with activity observed in their environment. Threat analytics supports investigation but does not by itself confirm that an organization has been compromised. Analysts should validate relevant indicators and behaviors against internal telemetry. The usefulness of the information also depends on the specific threat and the availability of current Microsoft threat research.<\/span><\/p>\n

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

                      Which KQL function counts the total number of records in a group?<\/b><\/p>\n

                        \n
                      1. dcount()<\/span><\/li>\n
                      2. count()<\/span><\/li>\n
                      3. avg()<\/span><\/li>\n
                      4. min()<\/span><\/li>\n<\/ol>\n

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

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

                        The KQL <\/span>count()<\/span> aggregation function counts records within the selected dataset or group. When used with <\/span>summarize<\/span>, it can show event frequency by fields such as username, device, application, or source IP. For example, <\/span>summarize count() by DeviceName<\/span> calculates the number of matching events for each device. Analysts commonly use this technique to identify unusually active entities or summarize security events. The result depends on the records included in the query, so analysts should apply appropriate filters and time ranges before interpreting high or low event counts.<\/span><\/p>\n

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

                        An analyst wants to identify all unique combinations of username and device in a dataset. Which KQL statement is appropriate?<\/b><\/p>\n

                          \n
                        1. summarize count() by Username<\/span><\/li>\n
                        2. project Username, DeviceName<\/span><\/li>\n
                        3. distinct Username, DeviceName<\/span><\/li>\n
                        4. order by Username<\/span><\/li>\n<\/ol>\n

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

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

                          The KQL <\/span>distinct<\/span> operator can return unique combinations of multiple columns. Using <\/span>distinct Username, DeviceName<\/span> produces each unique user-device combination found in the selected dataset without duplicate combinations. This can be useful when investigating which accounts accessed which endpoints or when creating a simplified list of relationships. The query does not indicate how frequently each combination occurred. If frequency is important, analysts should use <\/span>summarize count()<\/span> grouped by the same fields. The result should also be interpreted within the relevant time range and event type.<\/span><\/p>\n

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

                          Which Microsoft Defender for Endpoint capability allows an authorized analyst to interact with a device for investigation and response tasks?<\/b><\/p>\n

                            \n
                          1. Exposure management<\/span><\/li>\n
                          2. Live response<\/span><\/li>\n
                          3. Device discovery<\/span><\/li>\n
                          4. Secure Score<\/span><\/li>\n<\/ol>\n

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

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

                            Microsoft Defender for Endpoint Live Response provides authorized security personnel with capabilities for interacting with supported endpoints during investigations. Depending on permissions and available functionality, analysts can use it to perform response and investigation actions on a device. This can be valuable when collecting information or carrying out approved remediation steps without waiting for a user to provide access. Live Response should be used carefully because commands or actions can affect the endpoint. Organizations should apply appropriate permissions, maintain response procedures, and document actions taken during investigations.<\/span><\/p>\n

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

                            Which Microsoft Sentinel capability can help analysts visualize relationships between entities involved in an incident?<\/b><\/p>\n

                              \n
                            1. Investigation graph<\/span><\/li>\n
                            2. Data connector<\/span><\/li>\n
                            3. Watchlist<\/span><\/li>\n
                            4. Content hub<\/span><\/li>\n<\/ol>\n

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

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

                              The Microsoft Sentinel investigation graph can help analysts explore relationships between entities associated with an incident. Depending on available data, investigators may be able to examine connections involving users, devices, IP addresses, accounts, and other entities. This relationship-oriented view can provide additional context when investigating complex incidents and may help analysts identify related activity that is difficult to see in a simple alert list. The graph depends on the entities and telemetry available in the incident. Analysts should verify relationships against underlying events before treating them as evidence of malicious activity.<\/span><\/p>\n

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

                              Which KQL function calculates the number of distinct values approximately?<\/b><\/p>\n

                                \n
                              1. dcount()<\/span><\/li>\n
                              2. count()<\/span><\/li>\n
                              3. max()<\/span><\/li>\n
                              4. avg()<\/span><\/li>\n<\/ol>\n

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

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

                                The KQL <\/span>dcount()<\/span> function calculates an approximate distinct count. It is useful when analysts need to estimate the number of unique users, devices, IP addresses, or other values in large datasets. For example, <\/span>summarize dcount(AccountName)<\/span> can estimate how many unique accounts generated matching activity. Because the function is optimized for efficient processing, its result is approximate rather than an exact enumeration. Analysts should use it when that level of precision is appropriate. When exact unique results are required, a different query approach may be more suitable.<\/span><\/p>\n

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

                                Which Microsoft Sentinel feature is designed to detect suspicious activity by evaluating collected data against defined detection logic?<\/b><\/p>\n

                                  \n
                                1. Workbook<\/span><\/li>\n
                                2. Watchlist<\/span><\/li>\n
                                3. Analytics rule<\/span><\/li>\n
                                4. Playbook<\/span><\/li>\n<\/ol>\n

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

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

                                  Microsoft Sentinel analytics rules evaluate collected security data according to defined detection logic and can generate alerts or incidents when specified conditions are met. Rules can use KQL and different supported scheduling or detection approaches depending on their configuration. Analysts and administrators use analytics rules to identify suspicious activity and convert relevant telemetry into actionable security detections. Poorly designed rules can generate excessive false positives or miss important activity, so detection logic should be tested and tuned. Analysts should also monitor rule performance and review detections as threats and environments change.<\/span><\/p>\n

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

                                  Which KQL operator can filter results where a string field contains a specified sequence of characters?<\/b><\/p>\n

                                    \n
                                  1. order by<\/span><\/li>\n
                                  2. contains<\/span><\/li>\n
                                  3. summarize<\/span><\/li>\n
                                  4. project<\/span><\/li>\n<\/ol>\n

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

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

                                    The KQL <\/span>contains<\/span> operator can be used in a condition to determine whether a string field contains a specified sequence of characters. This can help analysts search for partial matches in fields such as command lines, filenames, URLs, or account names. For example, an analyst can filter events where a process command line contains a particular parameter. Analysts should understand the difference between string operators because exact matching and partial matching can produce different results. Broad <\/span>contains<\/span> searches may return many legitimate records, so additional conditions may be necessary.<\/span><\/p>\n

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

                                    Which Microsoft Defender XDR capability can correlate related alerts from multiple Microsoft security workloads into a unified incident?<\/b><\/p>\n

                                      \n
                                    1. Advanced hunting<\/span><\/li>\n
                                    2. Exposure management<\/span><\/li>\n
                                    3. Incident correlation<\/span><\/li>\n
                                    4. Secure Score<\/span><\/li>\n<\/ol>\n

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

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

                                      Microsoft Defender XDR correlates related alerts from supported security workloads to provide a more unified incident view. Instead of requiring analysts to investigate every alert independently, related signals can be associated with a broader incident when Microsoft determines they are connected. This can help analysts understand attack scope across identities, endpoints, email, and other supported workloads. Correlation does not eliminate the need for investigation because analysts should validate the relationships and review underlying evidence. A unified incident can provide useful context while still requiring careful triage and response.<\/span><\/p>\n

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

                                      Which KQL operator can order aggregated results from the highest value to the lowest value?<\/b><\/p>\n

                                        \n
                                      1. order by<\/span><\/li>\n
                                      2. where<\/span><\/li>\n
                                      3. extend<\/span><\/li>\n
                                      4. join<\/span><\/li>\n<\/ol>\n

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

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

                                        The KQL <\/span>order by<\/span> operator can sort query results according to a selected field. After using <\/span>summarize<\/span> to calculate values such as event counts, analysts can use descending order to place the highest values first. For example, aggregated authentication failures can be sorted so that accounts with the largest number of failures appear at the top. This is useful for prioritizing investigation results. Analysts should ensure that the aggregation is appropriate and that the selected time range is relevant before interpreting the highest values as suspicious.<\/span><\/p>\n

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

                                        A security team wants to automatically notify an analyst when a high-severity Sentinel incident is created. Which combination is most appropriate?<\/b><\/p>\n

                                          \n
                                        1. Watchlist and workbook<\/span><\/li>\n
                                        2. Analytics rule and device discovery<\/span><\/li>\n
                                        3. Automation rule and playbook<\/span><\/li>\n
                                        4. Content hub and data connector<\/span><\/li>\n<\/ol>\n

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

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

                                          A Microsoft Sentinel automation rule can identify incidents that meet conditions such as high severity, while a playbook can perform the notification workflow. The playbook can use Azure Logic Apps to send a message through a supported communication service or perform other configured actions. This combination separates the decision to trigger automation from the workflow that carries out the response. Administrators should test both components and ensure the notification contains useful incident context. Appropriate permissions and safeguards should also be configured to prevent unnecessary or repeated notifications.<\/span><\/p>\n

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

                                          View Full Microsoft SC-200 Exam Dumps and Practice Test Dumps. Question 361 Which Microsoft Sentinel component is responsible for collecting security data from external services and sources? Workbook Data connector Automation rule Watchlist Correct Answer: 2 Explanation Microsoft Sentinel data connectors provide integrations that bring data from supported Microsoft services, third-party products, and other sources […]<\/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\/15816"}],"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=15816"}],"version-history":[{"count":1,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/15816\/revisions"}],"predecessor-version":[{"id":15819,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/15816\/revisions\/15819"}],"wp:attachment":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/media?parent=15816"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/categories?post=15816"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/tags?post=15816"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}