DP-700 Practice Test 7 — 10 Questions

Question 1

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?

Accepted Answer

Replace 'SELECT *' with specific column names.. Selecting only the necessary columns (column projection) is a fundamental best practice in analytical query optimization. By avoiding 'SELECT *', you reduce the amount of data read from storage and transferred over the network. In column-oriented stores like those in Fabric, this allows the engine to only read the relevant columns, drastically reducing I/O and latency for queries on large datasets.

Answer

Increase the cluster memory size.

Answer

Add a clustered index to all columns.

Answer

Enable query parallelism.

Question 2

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)

Accepted Answer

The name of the operation and the item that triggered it.. The Timepoint Detail page is the most granular view in the Capacity Metrics app. It allows you to see exactly what was happening during a specific 30-second window when the capacity was under load. This detail is essential for identifying 'noisy neighbors' or specific jobs that are consuming more than their fair share of resources.

Answer

The physical IP address of the Spark executor nodes.

Answer

The SQL execution plan for every query in the timepoint.

Question 3

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

Accepted Answer

Implement Clustered Columnstore Indexes.. For read-heavy workloads in a data warehouse, indexing and proper table design are critical. Clustered Columnstore Indexes provide massive data compression and are optimized for analytical queries that scan large volumes of data. Additionally, implementing partitions allows the engine to prune data at the storage level, ensuring that only relevant partitions are scanned, thus reducing the total I/O and accelerating query execution.

Answer

Increase the number of rows per transaction.

Answer

Use row-based storage exclusively.

Answer

Disable data compression.

Question 4

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

Accepted Answer

Data Lineage. Data lineage provides a visual representation of the path data takes across a system. In Fabric, this is critical for debugging failures and understanding dependencies. By tracking lineage, you can quickly determine how a change in an upstream data source impacts downstream reports, facilitating better impact analysis and ensuring data quality across the entire analytical ecosystem.

Answer

Data Pipeline

Answer

OneLake

Answer

Notebook

Question 5

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?

Accepted Answer

Update the table statistics.. A Nested Loop Join is often inefficient for large datasets because it iterates through the outer table for every row in the inner table. If the optimizer chose a broadcast join on a large table, it might be due to outdated statistics. Updating statistics allows the query optimizer to make better decisions about join types, likely switching to a more efficient hash join that is better suited for large-scale data processing.

Answer

Increase the number of compute nodes.

Answer

Disable the query optimizer.

Answer

Rewrite the query using a cursor.

Question 6

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?

Accepted Answer

Use the metrics app to identify top-consuming items.. Before scaling up the capacity, you must identify the source of the high utilization. The Capacity Metrics app allows you to drill down into the operations that are consuming the most resources. By identifying the specific semantic models, reports, or users that are driving the high consumption of interactive operations, you can optimize those specific items, which may prevent the need for expensive upgrades to the capacity SKU.

Answer

Immediately scale up the capacity SKU.

Answer

Clear the browser cache for all users.

Answer

Delete all unused reports in the workspace.

Question 7

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?

Accepted Answer

The Workspace Monitor Hub. The Workspace Monitoring hub provides a centralized interface for viewing the activity of Spark-based items. By accessing the monitor tab, you can view job status, start times, and durations. This is vital for identifying long-running jobs that may be causing bottlenecks and for ensuring that automated pipeline runs are adhering to the expected time-to-completion service level agreements.

Answer

The Fabric Capacity Metrics App

Answer

Microsoft Purview Compliance Portal

Answer

The OneLake File Explorer

Question 8

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

Accepted Answer

The Fabric Capacity Metrics app. The Fabric Capacity Metrics app is the authoritative source for understanding how your consumption maps to billing. It translates technical usage metrics into visual reports that show how much compute you are using relative to your purchased SKU. This is critical for budget management and for identifying which departments or workspaces are the primary drivers of your organization's cloud expenditure.

Answer

The Microsoft Cost Management portal

Answer

Azure Advisor

Answer

The Fabric Admin Portal

Question 9

You are configuring a deployment pipeline to move a Lakehouse from a Test workspace to a Production workspace. Which THREE types of deployment rules can you apply to ensure the Lakehouse functions correctly in the Production environment?

Accepted Answer

Data source rules. Deployment rules are essential for tailoring Fabric items to their destination environment. For Lakehouses and semantic models, you can define rules that change the underlying data sources or parameters. This prevents the Production environment from accidentally referencing Test data and allows for a seamless transition that maintains data integrity and security across the lifecycle stages.

Answer

Lakehouse name rules

Answer

User permission rules

Question 10

Your organization uses Microsoft Fabric with three distinct workspaces for Development, Test, and Production. You need to automate the movement of a Lakehouse and its associated semantic model through these environments while ensuring that the Production environment uses a different data source connection string than the Development environment. Which feature should you implement?

Accepted Answer

Deployment Pipelines with Deployment Rules. Deployment pipelines in Microsoft Fabric provide a structured workflow for promoting content across environments. By using deployment rules, you can automatically update parameters such as connection strings or data source paths during the promotion process. This ensures that the Production environment remains isolated and points to the correct enterprise-grade data sources without requiring manual intervention or code changes.

Answer

Workspace Git Integration

Answer

OneLake Data Access Roles

Answer

Fabric REST API with Power BI Cmdlets