Databricks Certification Practice Test 09
Practice Test 09
Databricks Certification Practice Test 09
Practice Test 09
Insightful Saga — Modern Data Engineering Certification Preparation
Question 175
## Question 175 Statement 1: A Data Contract helps data producers and consumers agree on schema expectations. Statement 2: Data Contracts eliminate the need for data quality validation.
Data Contracts define expectations, but data quality validation is still required. ---
Question 176
## Question 176 Statement 1: A CI/CD pipeline can automate promotion of code between environments. Statement 2: Production deployments should always be performed manually.
CI/CD enables automated deployments. Manual deployment is not always required. ---
Question 177
## Question 177 Statement 1: Metadata helps users discover datasets. Statement 2: Metadata has no value for governance initiatives.
Question 178
## Question 178 Statement 1: Data Products should have clearly defined owners. Statement 2: Data Products should have defined SLAs.
Ownership and SLA definitions are both core data product principles. ---
Question 179
## Question 179 Statement 1: A business glossary helps standardize business terminology. Statement 2: Every department should define revenue independently.
Question 180
## Question 180 Statement 1: Observability helps engineers understand platform health. Statement 2: Observability is useful only after failures occur.
Observability is useful before, during and after incidents. ---
Question 181
## Question 181 Statement 1: Data lineage helps measure downstream impact of changes. Statement 2: Lineage information is useful during incident analysis.
Question 182
## Question 182 Statement 1: Data ownership improves accountability. Statement 2: Datasets without owners are easier to govern.
Question 183
## Question 183 Statement 1: Release approvals can reduce deployment risk. Statement 2: All code changes should go directly to production.
Question 184
## Question 184 Statement 1: Operational dashboards help monitor pipeline health. Statement 2: Operational dashboards replace logging.
Question 185
## Question 185 Statement 1: Domain teams are responsible for their data in Data Mesh. Statement 2: Data Mesh removes all governance requirements.
Question 186
## Question 186 Statement 1: A runbook helps responders handle production incidents. Statement 2: Runbooks can reduce incident resolution time.
Question 187
## Question 187 Statement 1: Monitoring can identify trends before failures occur. Statement 2: Monitoring should only focus on failed jobs.
Question 188
## Question 188 Statement 1: Dataset certification increases consumer confidence. Statement 2: Certification guarantees data can never contain errors.
Question 189
## Question 189 Statement 1: A semantic layer helps standardize business metrics. Statement 2: Semantic layers have no value for reporting consistency.
Question 190
## Question 190 Statement 1: Documentation supports onboarding new engineers. Statement 2: Documentation becomes unnecessary after deployment.
Question 191
## Question 191 Statement 1: Root Cause Analysis aims to identify underlying problems. Statement 2: Root Cause Analysis should focus only on symptoms.
Question 192
## Question 192 Statement 1: Alert fatigue can occur when excessive notifications are generated. Statement 2: Every informational event should trigger an alert.
Question 193
## Question 193 Statement 1: A service level objective helps define reliability expectations. Statement 2: Reliability targets should be measurable.
Question 194
## Question 194 Statement 1: Data stewardship supports governance goals. Statement 2: Data stewardship is unrelated to data quality.
Question 195
## Question 195 Statement 1: A platform team often provides shared capabilities for engineering teams. Statement 2: Each team should build its own governance framework independently.
Question 196
## Question 196 Statement 1: Impact analysis should occur before major schema changes. Statement 2: Consumer dependencies should be reviewed before deployment.
Question 197
## Question 197 Statement 1: Incident postmortems help organizations learn from failures. Statement 2: Postmortems should focus on assigning blame.
Question 198
## Question 198 Statement 1: Dataset discoverability improves self-service analytics. Statement 2: Searchable catalogs can improve discoverability.
Question 199
## Question 199 Statement 1: Data freshness can influence business decision-making. Statement 2: Refresh schedules should be documented.
Question 200
## Question 200 Statement 1: Standardized engineering practices improve maintainability. Statement 2: Reusable design patterns can reduce development effort.
Both practices improve scalability, consistency and long-term maintainability across enterprise data platforms. --- --- title: Databricks Certification Practice Test 10 description: Machine Learning and Lakehouse AI Scenario Questions ---