Monitor and Optimize an Analytics Solution

You are monitoring a Microsoft Fabric Lakehouse. You notice that queries against a specific Delta table are performing slowly despite the table having a small data size. You need to identify the root cause of the performance degradation. What should you examine first?

You are managing a Microsoft Fabric Capacity. You need to identify which two metrics are most effective for tracking the 'smoothing' behavior of your capacity during peak usage. Which two metrics should you monitor?

Refer to the exhibit. You are attempting to run an OPTIMIZE command with Z-ORDER on a large Lakehouse table. The operation fails with an InsufficientMemory error. What should you do to resolve this?

You are monitoring long-running Spark jobs in your Fabric workspace. You want to identify which specific stages of the job are consuming the most time. Which tool should you use?

You are optimizing a Fabric pipeline that processes data from a high-frequency sensor source. You notice significant data skew during the join operation. Which three strategies should you implement to mitigate this skew?

You notice that your Delta table is experiencing slow read performance due to file fragmentation. Which command should you run to optimize the physical storage layout?

You need to monitor the health and performance of your Microsoft Fabric environment. Which two components should you primarily monitor to identify bottlenecks in data movement?

Refer to the exhibit. The Spark job completed but took 45 minutes for a 100 million row dataset. The shuffle write size is significantly high. What should you investigate to improve performance?

You have a Fabric pipeline that runs a notebook. The notebook takes longer to start each time. What is the most likely cause?

Which Fabric tool allows you to visually track the total compute usage of your workspace over a specific timeframe?

You are monitoring an ingestion pipeline and notice it frequently fails with a 'Timeout' error. What is the most likely cause?

Which configuration would you adjust to improve the performance of a Spark job that is consistently failing due to 'Out of Memory' (OOM) errors during aggregation?

A Microsoft Fabric tenant is experiencing frequent throttling of background operations during the early morning hours. You have been tasked with identifying which specific items are consuming the most capacity units (CU) to determine if a workload needs to be rescheduled. Which tool should you use to get the most granular view of item-level CU consumption over a 14-day period?

Your organization uses a Fabric Spark notebook to process large volumes of streaming data into a Delta table. You notice that over time, query performance on the table is degrading significantly. Upon investigation, you find thousands of small files in the underlying OneLake folder. Which optimization strategy should you implement to resolve the performance issue while maintaining data integrity?

You are optimizing a complex data pipeline in Microsoft Fabric that includes several Data Factory activities and Spark notebooks. You need to reduce the overall execution time and resource consumption. Which TWO actions should you take? (Choose two.)

Refer to the exhibit. You are reviewing the capacity state for a production Fabric environment. Based on the JSON output from the monitoring API, what is the most likely impact on users and what should be your immediate action?

Refer to the exhibit. A data engineer is troubleshooting a Spark job that frequently fails with 'Out of Memory' (OOM) errors despite the configuration shown. The job processes a 500GB dataset with many wide transformations. What is the most effective configuration change to resolve the OOM errors?

You are monitoring a Dataflow Gen2 refresh that is failing intermittently. You need to identify if the failure is caused by a data type mismatch or a timeout from the source system. Which TWO actions will help you find the specific error details? (Choose two.)

You want to automate the monitoring of your Fabric Capacity and receive a notification on your mobile device whenever the capacity utilization exceeds 90% for more than 15 minutes. Which Microsoft Fabric feature should you use to implement this alert?

Your team is using a Fabric Lakehouse to store Parquet files. You notice that the storage costs are increasing faster than expected, and there are many old versions of the data being retained. Which maintenance task should you schedule to optimize OneLake storage costs without affecting the current production data?

A Power BI report using a semantic model in 'Direct Lake' mode is performing poorly. You want to determine if the queries are falling back to 'DirectQuery' mode due to memory constraints or unsupported DAX features. Which tool is best suited for this specific optimization task?

You are managing a large-scale data ingestion pipeline that runs every hour. Recently, the pipeline has started to fail with 'Concurrency Limit Exceeded' errors. You have several other pipelines running in the same workspace. How should you optimize the environment to resolve this error?

Refer to the exhibit. You are reviewing the monitoring logs for your Fabric capacity. What is the most likely cause of the error shown in the exhibit?

You want to monitor the health and performance of your Microsoft Fabric pipelines. Which tool should you use to view detailed execution logs and identify bottlenecks in your data movement?

Which THREE features are provided by the Fabric Capacity Metrics app for monitoring performance?

You are optimizing a Spark job in a Fabric notebook that joins a large fact table with a small dimension table. The join operation is causing high memory usage and slow performance. What technique should you implement?

Your organization uses Power BI in Fabric. Users report that reports are slow to load. You want to identify which specific visuals are causing the performance bottleneck. Which tool should you use?

You are optimizing a Data Warehouse in Microsoft Fabric. Which TWO strategies will effectively improve the performance of read-heavy workloads?

Refer to the exhibit. The refresh operation for a Power BI semantic model took 45 minutes to complete. What is the most efficient way to reduce the refresh time for this specific model?

You have a Fabric notebook that uses multiple Spark libraries. You notice that the startup time for your notebook is very slow. What is the best way to optimize this?

You are troubleshooting a slow-running SQL query in a Fabric Data Warehouse. The query plan shows a high cost associated with a 'Broadcast Nested Loop Join'. What should you do to optimize this?

When monitoring Fabric Data Pipelines, which TWO metrics are most useful for identifying performance issues in data copy activities?

Refer to the exhibit. The query is performing a full table scan on a 1TB table. What is the most effective way to optimize this query?

You are using the Microsoft Fabric Capacity Metrics app and notice that your capacity is frequently hitting the limit for 'Interactive' operations. What should you do first?

You are monitoring a Spark notebook in Microsoft Fabric that is taking longer than expected to process a large dataset. You notice that a single executor is processing significantly more data than others. Which tool or feature should you use to identify the specific partition causing this data skew?

You need to quickly identify all failed Data Factory pipeline runs and Spark jobs across multiple workspaces in your Microsoft Fabric environment. Which TWO actions should you perform in the Fabric Monitoring Hub?

Refer to the exhibit. You are reviewing the execution plan for a query running on a Fabric SQL Analytics Endpoint. The query is performing slower than expected. Based on the JSON snippet of the plan, what is the most likely cause of the performance bottleneck?

A Data Factory pipeline in Fabric fails during the execution of a Copy activity. You need to find the specific error message and the number of rows successfully written before the failure. Where should you look?

You are tasked with optimizing the performance of a Delta table in a Fabric Lakehouse that is queried frequently by both Spark notebooks and the SQL Analytics Endpoint. Which TWO techniques should you use to improve data skipping and read performance?

You are configuring a Spark pool in Microsoft Fabric for a workload with highly variable data volumes. You want to ensure that the pool can handle peak loads without over-provisioning resources during quiet periods. Which setting should you adjust?

In Microsoft Fabric, you notice that a background job (such as a Dataflow refresh) is taking significantly longer than usual, even though the total Capacity Unit (CU) usage is below the limit. What is the most likely cause of this behavior based on Fabric's capacity management rules?

You are using a KQL Database in a Microsoft Fabric Eventhouse to analyze streaming data. You need to monitor the performance of your Kusto queries and identify which ones are consuming the most resources. Which TWO methods should you use?

Refer to the exhibit. You are reviewing the configuration for a Fabric Spark Environment. A job is failing with an 'OutOfMemoryError' during a large shuffle operation. Based on the configuration, which change would most likely resolve the issue?

You are auditing data access in a Microsoft Fabric workspace and notice unexpected 'Access Denied' errors in the OneLake logs for a service principal that should have read-only access. The service principal has the 'Viewer' role in the workspace. What is the most likely cause?

You are analyzing a performance bottleneck using the 'Timepoint Detail' page in the Fabric Capacity Metrics app. Which THREE pieces of information can you find here to help identify the specific cause of a capacity overage? (Select THREE)

You are monitoring a Dataflow Gen2 refresh in Microsoft Fabric. The refresh fails with an error: 'Mashup Evaluation Error'. What is the most common cause of this error when working with large datasets in Dataflows?

You need to monitor the historical performance of queries in a Fabric Warehouse to identify which ones frequently use the most CPU time. Which Dynamic Management View (DMV) should you query?

You are monitoring a Microsoft Fabric Lakehouse. You observe that queries against a specific Delta table are performing poorly. You identify that the table contains a large number of small files. Which command should you run to optimize the file layout?

You are managing a Microsoft Fabric capacity. You need to identify which users are consuming the most compute resources and determine if any throttled requests are occurring. Which TWO tools should you use?

Refer to the exhibit. You are reviewing pipeline logs and notice the 429 error. What is the most appropriate long-term action to prevent this?

Which feature in Microsoft Fabric allows you to track the movement and transformation of data from source to destination?

You are auditing a Fabric workspace to ensure optimal performance. You want to see the execution history and duration of all Spark notebooks run within the last 30 days. Where should you look?

You are troubleshooting a slow-running Power BI report connected to a Fabric Semantic Model. What is the most effective way to identify the bottleneck?

You need to minimize the performance impact of concurrent data refreshes on your Fabric capacity. What is the best strategy?

Which tool in Fabric provides the most detailed view of the billable capacity usage for your tenant?

When a Spark notebook job finishes, what is the best practice for managing the underlying compute cluster resources?