{"id":11987,"date":"2026-09-15T05:21:22","date_gmt":"2026-09-15T05:21:22","guid":{"rendered":"https:\/\/www.examlabs.com\/certification\/?p=11987"},"modified":"2026-09-15T05:21:22","modified_gmt":"2026-09-15T05:21:22","slug":"servicenow-cis-df-practice-test-questions-and-exam-dumps-part14-q261-280","status":"publish","type":"post","link":"https:\/\/www.examlabs.com\/certification\/servicenow-cis-df-practice-test-questions-and-exam-dumps-part14-q261-280\/","title":{"rendered":"ServiceNow CIS-DF Practice Test Questions and Exam Dumps Part14 Q261-280"},"content":{"rendered":"

View Full\u00a0ServiceNow CIS-DF Exam Dumps<\/a>\u00a0and Practice Test Dumps.<\/b><\/h2>\n

 <\/p>\n

Question 261<\/b><\/h3>\n

What is the primary purpose of a business glossary in data governance?<\/b><\/p>\n

    \n
  1. To store system passwords<\/span><\/li>\n
  2. To define and standardize business terms<\/span><\/li>\n
  3. To delete obsolete records<\/span><\/li>\n
  4. To monitor server performance<\/span><\/li>\n<\/ol>\n

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

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

    A business glossary provides agreed definitions for important business terms used across an organization. It helps ensure that teams understand terms consistently when creating, reporting, integrating, or analyzing data. For example, a glossary can define what an \u201cactive customer\u201d or \u201ccritical service\u201d means according to approved business rules. In ServiceNow data governance, standardized terminology reduces semantic inconsistencies and supports better communication between technical and business teams. A well-maintained glossary can also support data ownership, quality rules, metadata management, and reporting consistency.<\/span><\/p>\n

    Question 262<\/b><\/h3>\n

    Which governance artifact defines mandatory organizational requirements for managing data?<\/b><\/p>\n

      \n
    1. Data policy<\/span><\/li>\n
    2. Data dashboard<\/span><\/li>\n
    3. Data profile<\/span><\/li>\n
    4. Data extract<\/span><\/li>\n<\/ol>\n

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

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

      A data policy establishes mandatory organizational requirements and expectations for how data should be managed. Policies can address areas such as ownership, quality, classification, access, retention, or acceptable use. In a ServiceNow governance environment, policies provide a high-level foundation that can be supported by more detailed standards and procedures. Policies should be approved by appropriate governance authorities and communicated to relevant stakeholders. Unlike informal recommendations, policies establish requirements that organizations can monitor for compliance and use as a basis for governance decisions.<\/span><\/p>\n

      Question 263<\/b><\/h3>\n

      Which document normally provides detailed mandatory requirements for implementing a data policy?<\/b><\/p>\n

        \n
      1. Business glossary<\/span><\/li>\n
      2. Data standard<\/span><\/li>\n
      3. Data dashboard<\/span><\/li>\n
      4. Data catalog search<\/span><\/li>\n<\/ol>\n

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

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

        A data standard translates broader policy requirements into specific, measurable, and mandatory expectations. For example, a policy may require consistent customer identification, while a standard can specify acceptable formats, required attributes, or approved values. In ServiceNow data governance, standards provide implementation guidance that teams can apply consistently across systems and processes. Standards are more specific than policies and can be used when defining validation rules, integration requirements, naming conventions, or quality thresholds. This distinction helps organizations maintain a structured governance framework.<\/span><\/p>\n

        Question 264<\/b><\/h3>\n

        What is a major benefit of maintaining a data catalog?<\/b><\/p>\n

          \n
        1. It improves discoverability and understanding of available data<\/span><\/li>\n
        2. It automatically corrects every data error<\/span><\/li>\n
        3. It eliminates the need for data owners<\/span><\/li>\n
        4. It prevents all data access<\/span><\/li>\n<\/ol>\n

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

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

          A data catalog helps users discover available data assets and understand important information about them. Catalog entries can include descriptions, owners, classifications, metadata, lineage, quality information, and usage context. In a ServiceNow environment, better discoverability can help users identify appropriate sources instead of creating duplicate or conflicting datasets. A catalog does not automatically fix data quality problems, but it provides visibility into available information and its characteristics. This supports informed data usage, governance decisions, impact analysis, and collaboration between business and technical stakeholders.<\/span><\/p>\n

          Question 265<\/b><\/h3>\n

          Which role is primarily responsible for making business decisions about a data domain?<\/b><\/p>\n

            \n
          1. Data consumer<\/span><\/li>\n
          2. Data owner<\/span><\/li>\n
          3. Database administrator<\/span><\/li>\n
          4. Report viewer<\/span><\/li>\n<\/ol>\n

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

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

            A data owner is typically accountable for business-level decisions concerning a data domain, including definitions, quality expectations, access considerations, and governance requirements. The owner may delegate operational activities to data stewards while retaining overall accountability. In ServiceNow data governance, clearly defining the owner helps establish decision rights and provides an escalation point for significant issues. The owner does not necessarily perform technical maintenance personally. Instead, the role focuses on ensuring that the data supports business needs and is governed according to approved organizational requirements.<\/span><\/p>\n

            Question 266<\/b><\/h3>\n

            Which activity is most appropriate for a data steward?<\/b><\/p>\n

              \n
            1. Defining corporate strategy for unrelated applications<\/span><\/li>\n
            2. Performing day-to-day data quality monitoring and issue coordination<\/span><\/li>\n
            3. Replacing all database administrators<\/span><\/li>\n
            4. Approving employee salaries<\/span><\/li>\n<\/ol>\n

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

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

              Data stewards commonly perform operational activities that support data quality and governance. Their responsibilities can include monitoring quality results, investigating issues, coordinating remediation, maintaining definitions, and helping users follow established standards. In ServiceNow, a steward may work with data owners, technical teams, and business users to resolve data problems and maintain governance practices. The steward generally operates within the policies and decisions established by data owners or governance authorities. This role helps convert governance requirements into consistent day-to-day data management activities.<\/span><\/p>\n

              Question 267<\/b><\/h3>\n

              What is the main purpose of a data contract between systems?<\/b><\/p>\n

                \n
              1. To define agreed expectations for exchanged data<\/span><\/li>\n
              2. To replace all security controls<\/span><\/li>\n
              3. To prevent source systems from being upgraded<\/span><\/li>\n
              4. To eliminate data ownership<\/span><\/li>\n<\/ol>\n

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

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

                A data contract defines agreed expectations between systems or teams regarding exchanged information. It may describe fields, formats, meanings, required values, validation expectations, and change responsibilities. For ServiceNow integrations, a clear contract can reduce misunderstandings between source and target teams and make changes easier to manage. When an interface changes, teams can evaluate whether the proposed change remains compatible with the agreed contract. This supports reliable integrations and helps prevent unexpected data quality problems caused by undocumented changes in structure or meaning.<\/span><\/p>\n

                Question 268<\/b><\/h3>\n

                Which data classification approach best supports risk-based governance?<\/b><\/p>\n

                  \n
                1. Treating every data element identically<\/span><\/li>\n
                2. Classifying information according to sensitivity and business impact<\/span><\/li>\n
                3. Allowing users to choose classifications randomly<\/span><\/li>\n
                4. Classifying only records that contain errors<\/span><\/li>\n<\/ol>\n

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

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

                  Classifying information according to sensitivity and business impact allows organizations to apply controls proportionate to risk. Not all data requires the same level of protection, monitoring, or governance. In ServiceNow, classification can help determine appropriate access, handling, retention, and oversight requirements. Higher-risk or more sensitive information may require stronger controls and more frequent reviews. A consistent classification framework also improves communication because users can understand the expected handling requirements for different categories of information instead of applying inconsistent rules.<\/span><\/p>\n

                  Question 269<\/b><\/h3>\n

                  What should happen when a data quality exception is approved?<\/b><\/p>\n

                    \n
                  1. It should be documented with its scope, reason, owner, and review expectations<\/span><\/li>\n
                  2. It should remain undocumented<\/span><\/li>\n
                  3. All validation rules should be removed<\/span><\/li>\n
                  4. The entire dataset should be deleted<\/span><\/li>\n<\/ol>\n

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

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

                    An approved data quality exception should be documented so that stakeholders understand why the normal requirement is temporarily or permanently not being met. Documentation should identify the affected data, reason for the exception, responsible owner, applicable scope, and review or expiration expectations when appropriate. In ServiceNow governance, controlled exceptions prevent legitimate business cases from being confused with uncontrolled quality failures. They also provide an audit trail and help teams determine whether an exception remains justified. Exceptions should be reviewed periodically to prevent unnecessary permanent deviations from standards.<\/span><\/p>\n

                    Question 270<\/b><\/h3>\n

                    Which metric would best measure the proportion of records containing all required attributes?<\/b><\/p>\n

                      \n
                    1. Timeliness rate<\/span><\/li>\n
                    2. Completeness rate<\/span><\/li>\n
                    3. Uniqueness rate<\/span><\/li>\n
                    4. Accuracy rate<\/span><\/li>\n<\/ol>\n

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

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

                      A completeness rate measures how much required information is present within the evaluated dataset. If an organization requires specific attributes to be populated, the completeness metric can calculate the proportion of records meeting those requirements. In ServiceNow data quality management, completeness rules should clearly identify the required fields and the population being measured. This prevents misleading results caused by including irrelevant records. Completeness is different from accuracy because a field may be populated but still contain an incorrect value. Both dimensions may therefore require separate quality measures.<\/span><\/p>\n

                      Question 271<\/b><\/h3>\n

                      Why should a data quality metric specify its population?<\/b><\/p>\n

                        \n
                      1. To ensure the measurement applies to the intended set of records<\/span><\/li>\n
                      2. To increase the number of records automatically<\/span><\/li>\n
                      3. To avoid defining the metric<\/span><\/li>\n
                      4. To make every record pass validation<\/span><\/li>\n<\/ol>\n

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

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

                        Defining the metric population ensures that the measurement evaluates the correct records and produces meaningful results. For example, a quality rule may apply only to active configuration items rather than retired or archived records. If unrelated records are included, the resulting percentage may incorrectly represent actual quality performance. In ServiceNow, clearly documented populations improve consistency between dashboards, reports, and governance reviews. They also make it easier to compare results over time because stakeholders know exactly which records were evaluated when interpreting changes in the metric.<\/span><\/p>\n

                        Question 272<\/b><\/h3>\n

                        What is the main advantage of using controlled values for important categorical fields?<\/b><\/p>\n

                          \n
                        1. They reduce variations caused by inconsistent user-entered values<\/span><\/li>\n
                        2. They guarantee that records are accurate<\/span><\/li>\n
                        3. They eliminate the need for ownership<\/span><\/li>\n
                        4. They prevent all integrations<\/span><\/li>\n<\/ol>\n

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

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

                          Controlled values restrict users or processes to an approved set of choices for categorical information. This reduces variations such as different spellings, abbreviations, or unofficial categories representing the same concept. In ServiceNow, controlled values can improve consistency in reporting, filtering, integrations, and automation. However, controlled values do not guarantee accuracy because users may still select the wrong approved value. They should therefore be combined with appropriate definitions, validation, ownership, and monitoring. Proper maintenance is also important when legitimate business categories change.<\/span><\/p>\n

                          Question 273<\/b><\/h3>\n

                          Which condition represents a referential integrity problem?<\/b><\/p>\n

                            \n
                          1. A record contains an approved status<\/span><\/li>\n
                          2. A reference field points to a record that no longer exists<\/span><\/li>\n
                          3. A field contains a current date<\/span><\/li>\n
                          4. A required field contains a valid value<\/span><\/li>\n<\/ol>\n

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

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

                            A referential integrity problem occurs when a relationship between records is invalid or broken. For example, a reference field may point to a record that has been deleted, is unavailable, or is otherwise invalid. In ServiceNow, relationships between records can be important for reporting, automation, workflows, and service management processes. Broken references can therefore cause incomplete information or unexpected system behavior. Monitoring relationship integrity helps identify orphaned references and ensures that related records continue to point to valid and appropriate targets.<\/span><\/p>\n

                            Question 274<\/b><\/h3>\n

                            What is an orphaned record in a relational data structure?<\/b><\/p>\n

                              \n
                            1. A record that has no valid required parent or related record<\/span><\/li>\n
                            2. A record with a unique identifier<\/span><\/li>\n
                            3. A record containing all required values<\/span><\/li>\n
                            4. A record created through an approved process<\/span><\/li>\n<\/ol>\n

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

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

                              An orphaned record is a record that has lost a required relationship to its expected parent or related record. For example, a child record may remain after the parent record has been removed or becomes unavailable. In ServiceNow, orphaned records can reduce data consistency and make reporting or automation unreliable. Identifying these records requires examining relationship rules and expected dependencies. Remediation may involve restoring the correct relationship, updating the record, or removing it when appropriate according to approved lifecycle and governance requirements.<\/span><\/p>\n

                              Question 275<\/b><\/h3>\n

                              Which control is considered preventive rather than detective?<\/b><\/p>\n

                                \n
                              1. Reviewing a quality dashboard after records are created<\/span><\/li>\n
                              2. Blocking invalid values during data entry<\/span><\/li>\n
                              3. Measuring duplicate records monthly<\/span><\/li>\n
                              4. Investigating errors after an integration<\/span><\/li>\n<\/ol>\n

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

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

                                A preventive control attempts to stop a data quality problem before incorrect information enters or moves through the system. Blocking invalid values during data entry is an example because the user or process cannot submit information that violates the defined requirement. Detective controls, by contrast, identify problems after they occur through monitoring, reporting, or audits. In ServiceNow, combining preventive and detective controls provides stronger governance. Preventive controls reduce the creation of errors, while detective controls help identify problems that bypass or occur outside preventive mechanisms.<\/span><\/p>\n

                                Question 276<\/b><\/h3>\n

                                Which practice is most effective for managing a change to an important data definition?<\/b><\/p>\n

                                  \n
                                1. Change the definition without notifying users<\/span><\/li>\n
                                2. Assess impact, obtain approval, and communicate the change<\/span><\/li>\n
                                3. Delete previous definitions immediately<\/span><\/li>\n
                                4. Allow every team to use its own meaning<\/span><\/li>\n<\/ol>\n

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

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

                                  Changes to important data definitions can affect reports, integrations, quality rules, workflows, and business decisions. A controlled process should therefore assess potential impacts, obtain appropriate approval, update governance documentation, and communicate the new definition to affected stakeholders. In ServiceNow, this approach helps prevent different teams from continuing to use conflicting meanings after a definition changes. Impact analysis is particularly important when the term is used widely across applications. Controlled definition management supports consistency, traceability, and predictable behavior across the data environment.<\/span><\/p>\n

                                  Question 277<\/b><\/h3>\n

                                  What is the primary benefit of retaining historical data quality measurements?<\/b><\/p>\n

                                    \n
                                  1. It allows organizations to identify trends and evaluate improvement<\/span><\/li>\n
                                  2. It prevents all future data errors<\/span><\/li>\n
                                  3. It removes the need for baselines<\/span><\/li>\n
                                  4. It guarantees accurate source data<\/span><\/li>\n<\/ol>\n

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

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

                                    Retaining historical data quality measurements allows organizations to compare current performance with previous periods. This makes it possible to identify trends, determine whether remediation produced lasting improvements, and detect gradual deterioration. In ServiceNow, historical metrics can support governance reviews and help teams evaluate whether quality targets are being achieved consistently. Without historical information, a current score may have little context. Trend analysis is especially useful for critical data because it can reveal recurring issues that may require preventive action rather than repeated record-level correction.<\/span><\/p>\n

                                    Question 278<\/b><\/h3>\n

                                    Which factor should most influence the priority assigned to a data quality issue?<\/b><\/p>\n

                                      \n
                                    1. The color of the dashboard<\/span><\/li>\n
                                    2. Business impact and risk<\/span><\/li>\n
                                    3. The number of people viewing the report<\/span><\/li>\n
                                    4. The age of the database<\/span><\/li>\n<\/ol>\n

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

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

                                      Business impact and risk should strongly influence the priority assigned to a data quality issue. A problem affecting a critical service, regulatory requirement, or major business process may require immediate attention even if it affects relatively few records. Conversely, a larger issue with limited business impact may receive a lower priority. In ServiceNow governance, risk-based prioritization helps teams use remediation resources effectively. Factors such as affected population, criticality, downstream dependencies, and operational consequences can be considered when determining the appropriate response.<\/span><\/p>\n

                                      Question 279<\/b><\/h3>\n

                                      Why is traceability important in data governance?<\/b><\/p>\n

                                        \n
                                      1. It helps show where data originated, how it changed, and how it is used<\/span><\/li>\n
                                      2. It eliminates the need for data owners<\/span><\/li>\n
                                      3. It guarantees that every record is accurate<\/span><\/li>\n
                                      4. It prevents data from being shared<\/span><\/li>\n<\/ol>\n

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

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

                                        Traceability provides visibility into the history and movement of information. It can help organizations understand where data originated, what transformations were applied, where it was stored, and how it reached downstream consumers. In ServiceNow, traceability supports troubleshooting, audits, impact analysis, and data quality investigations. When a value appears incorrect, teams can use traceability information to investigate the source and transformation path instead of examining the final record alone. Strong traceability therefore improves accountability and makes data-related decisions easier to support with evidence.<\/span><\/p>\n

                                        Question 280<\/b><\/h3>\n

                                        Which activity best supports periodic recertification of an important data source?<\/b><\/p>\n

                                          \n
                                        1. Confirming ownership, quality performance, usage, and continued business need<\/span><\/li>\n
                                        2. Automatically approving the source forever<\/span><\/li>\n
                                        3. Removing all source documentation<\/span><\/li>\n
                                        4. Ignoring previous quality results<\/span><\/li>\n<\/ol>\n

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

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

                                          Periodic recertification confirms that an important data source remains appropriate for its intended purpose. The review can consider whether ownership is still valid, quality targets are being met, the source is still actively used, and the business continues to rely on it. In ServiceNow governance, recertification can also identify outdated sources, unresolved quality concerns, or changes in business requirements. Regular review prevents sources from remaining trusted indefinitely without evidence. It supports stronger governance by ensuring that important data assets continue to meet established expectations.<\/span><\/p>\n

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

                                          View Full\u00a0ServiceNow CIS-DF Exam Dumps\u00a0and Practice Test Dumps.   Question 261 What is the primary purpose of a business glossary in data governance? To store system passwords To define and standardize business terms To delete obsolete records To monitor server performance Correct Answer: 2 Explanation A business glossary provides agreed definitions for important business terms […]<\/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\/11987"}],"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=11987"}],"version-history":[{"count":1,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/11987\/revisions"}],"predecessor-version":[{"id":12005,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/11987\/revisions\/12005"}],"wp:attachment":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/media?parent=11987"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/categories?post=11987"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/tags?post=11987"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}