Databricks Certification Practice Test 07
Practice Test 07
Databricks Certification Practice Test 07
Practice Test 07
Insightful Saga — Modern Data Engineering Certification Preparation
Question 111
## Question 111 A company wants to improve reliability of production ETL pipelines. Which TWO practices should be implemented?
Data quality checks prevent bad data. Monitoring and alerting help detect failures quickly. ---
Question 112
## Question 112 Which TWO actions trigger Spark execution?
count() and collect() are actions. Spark executes the DAG only when an action occurs. ---
Question 113
## Question 113 Which TWO operations are considered wide transformations?
Wide transformations require shuffling data between partitions. ---
Question 114
## Question 114 Which TWO metrics should a Data Engineer monitor during workload tuning?
Question 115
## Question 115 A company wants code promotions from Dev → QA → Prod. Which TWO capabilities support this process?
Question 116
## Question 116 Which TWO benefits are provided by Delta Live Tables?
Question 117
## Question 117 A Data Engineer wants to reduce cloud costs. Which TWO actions are recommended?
Question 118
## Question 118 Which TWO datasets are usually suitable for caching?
Question 119
## Question 119 A Spark job processes customer records. Which TWO factors can cause performance degradation?
Question 120
## Question 120 Which TWO activities belong to Data Governance?
Question 121
## Question 121 Which TWO features help improve discoverability of datasets?
Question 122
## Question 122 Which TWO attributes make a dataset trusted?
Question 123
## Question 123 A company wants to audit data access. Which TWO details are important?
Question 124
## Question 124 Which TWO tasks are commonly automated in ETL platforms?
Question 125
## Question 125 Which TWO indicators suggest a pipeline requires optimization?
Question 126
## Question 126 Which TWO benefits come from partition pruning?
Question 127
## Question 127 A production deployment failed. Which TWO capabilities help rollback changes?
Question 128
## Question 128 Which TWO characteristics are associated with streaming systems?
Question 129
## Question 129 Which TWO business benefits come from data lineage?
Question 130
## Question 130 An organization follows medallion architecture. Which TWO responsibilities belong in Gold?
Question 131
## Question 131 Which TWO techniques help reduce data duplication?
Question 132
## Question 132 Which TWO things should a support engineer check first when a workflow fails?
Question 133
## Question 133 A company wants SLA compliance. Which TWO metrics are most important?
Question 134
## Question 134 Which TWO practices improve maintainability?
Question 135
## Question 135 Which TWO characteristics define a production-ready pipeline?
Question 136
## Question 136 Which TWO activities are part of root cause analysis?
Question 137
## Question 137 Which TWO factors influence cluster sizing?
Question 138
## Question 138 A data product is consumed by multiple teams. Which TWO things should exist?
Question 139
## Question 139 Which TWO goals are achieved through standard schemas?
Question 140
## Question 140 Which TWO areas should be included in production monitoring?
Question 141
## Question 141 Which TWO symptoms suggest under-partitioning?
Question 142
## Question 142 Which TWO activities improve platform security?
Question 143
## Question 143 Which TWO practices improve data trustworthiness?
Question 144
## Question 144 Which TWO reasons justify workflow retries?
Question 145
## Question 145 Which TWO items should be documented for datasets?
Question 146
## Question 146 Which TWO principles support Data Mesh initiatives?
Question 147
## Question 147 Which TWO indicators show healthy operations?
Question 148
## Question 148 Which TWO components should be considered before deleting production data?
Question 149
## Question 149 Which TWO benefits come from reusable ETL frameworks?
Question 150
## Question 150 Which TWO skills are most important for a Senior Data Engineer?
Question 151
## Question 151 A global retail company processes customer transactions from stores located in 50 countries. The company currently experiences the following issues: - Duplicate customer records - Inconsistent product naming - Missing customer identifiers - Frequent downstream reporting failures The data engineering team is redesigning the Silver layer to improve overall data quality and reliability. Which actions should be implemented?
Silver layer responsibilities include: - Cleansing - Deduplication - Standardization - Validation - Data quality enforcement Executive dashboards belong to Gold. Raw files belong to Bronze.
Question 152
Question 152 A large airline company runs a nightly Databricks workflow that occasionally misses its SLA because processing times fluctuate significantly between executions. Investigation reveals: Uneven data distribution Large shuffle operations Rapid growth in data volume Which actions may help improve performance? Review partition strategy Analyze shuffle metrics Investigate skewed keys Increase dashboard refresh rate Evaluate Adaptive Query Execution Rename notebook files
All four actions directly address Spark execution bottlenecks.
Question 153
Question 153 A healthcare company stores highly sensitive patient information in Databricks. Security auditors require stronger governance controls. Which controls should be considered? Least privilege access Data classification Access auditing Open permissions for all users Periodic access reviews Shared administrator accounts
These are standard governance and security controls for regulated environments.
Question 154
Question 154 A newly hired Data Engineer reviews an ETL framework that is used by dozens of pipelines across the organization. The engineering manager wants future pipelines to be easier to maintain. Which practices support maintainability? Modular code Reusable components Consistent naming conventions Copy-paste transformations Documentation standards Hardcoded parameters
Question 155
Question 155 An e-commerce company plans to create a trusted enterprise data platform. Business users often complain that reports from different departments show different revenue numbers. Which actions help establish a trusted data foundation? Define common business metrics Assign dataset ownership Implement data quality validation Allow independent metric definitions Document data definitions Eliminate governance reviews
Question 156
Question 156 A support engineer is troubleshooting a failed production workflow. Which information should be reviewed first? Error messages Task execution history Pipeline logs Cluster resource utilization User profile pictures Dashboard color themes
Question 157
Question 157 A manufacturing company expects IoT data volume to triple during the next year. The architecture team wants to ensure scalability. Which factors should be evaluated? Growth projections Storage strategy Processing capacity Cost management Employee parking spaces Office seating plans
Question 158
Question 158 A company wants better operational visibility across all production pipelines. Which capabilities should be implemented? Alerting Monitoring dashboards SLA tracking Failure notifications Random notebook execution Manual health checks only
Question 159
Question 159 A global bank is preparing for a regulatory audit. Which metadata information would auditors likely consider valuable? Data owners Data lineage Access history Dataset classifications Wallpaper configuration Browser themes
Question 160
Question 160 A company wants to build data products that can be safely consumed by multiple business units. Which characteristics should those products have? Clear ownership Documentation Quality controls Defined SLAs Unknown refresh schedule Inconsistent schema