DP-203 Matching — 10 Questions

Question 1

Match each Azure data integration tool to its typical use case.

Accepted Answer

Azure Data Factory: Orchestrate and automate data movement and transformation at scale.. In this matching exercise, the correct pairs are: Azure Data Factory for orchestration, Azure Synapse Analytics for data warehousing, Azure Databricks for data engineering/ML, and Azure Stream Analytics for real-time streaming. Common confusions involve swapping orchestration and streaming roles.

Answer

Azure Data Factory: Process real-time streaming data from IoT devices.

Answer

Azure Synapse Analytics: Orchestrate data movement at scale.

Question 2

Match each Azure service to its primary purpose in a data engineering pipeline.

Accepted Answer

Azure Data Lake Storage Gen2: Scalable data lake for big data analytics.. The correct matches are: Azure Data Lake Storage Gen2 as a scalable data lake, Azure Synapse Analytics as a unified data warehousing platform, Azure Data Factory for data integration and orchestration, and Azure Databricks for Spark-based analytics. Common confusions include swapping storage and integration services, or mistaking data lakes for data warehousing.

Answer

Azure Data Lake Storage Gen2: Cloud data integration service for orchestrating data movement.

Answer

Azure Synapse Analytics: Scalable data lake for big data analytics.

Question 3

Match each Azure Synapse Analytics component to its function.

Accepted Answer

Dedicated SQL pool: Provisioned compute resources for high-performance querying of relational data.. In Azure Synapse Analytics, Dedicated SQL pool provides provisioned compute for relational data, Serverless SQL pool queries data lake files on-demand, Apache Spark pool handles distributed processing with Spark, and Pipeline orchestrates workflows. Common confusions include mixing serverless and provisioned capabilities or attributing Spark functionality to SQL pools.

Answer

Dedicated SQL pool: Serverless querying of data in data lake.

Answer

Serverless SQL pool: Managed Spark clusters for big data analytics.

Question 4

Match each Azure security feature to its description.

Accepted Answer

Azure Active Directory: A cloud-based identity and access management service that provides authentication and authorization.. The correct matches are: Azure AD for identity and access management, Key Vault for secrets management, RBAC for fine-grained access control, and Managed Identity for automatically managed identities. Common confusions include swapping Azure AD with Managed Identity and Key Vault with RBAC.

Answer

Azure Active Directory: An automatically managed identity in Azure AD for applications to connect to resources without managing credentials.

Answer

Azure Key Vault: A service that provides role-based access control for Azure resources.

Question 5

Match each performance optimization technique to its description.

Accepted Answer

Columnstore Indexes: Improves query performance by storing data in columnar format, allowing better compression and faster scanning.. Correct matches: Columnstore indexes improve scan performance via columnar storage; partition switching enables fast data segment movement; materialized views pre-compute aggregations; result set caching caches query results. Common confusions include swapping partition switching with columnstore indexes or materialized views with result set caching.

Answer

Columnstore Indexes: Enables fast loading and removal of large data segments.

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Materialized Views: Stores query results in cache to reuse for repeated queries.

Question 6

Match each data storage format to its characteristic.

Accepted Answer

Parquet: Columnar storage format, efficient for analytics and compression. In Azure data engineering, Parquet and ORC are columnar formats ideal for analytics, while Avro is row-based with embedded schema, and JSON is a semi-structured text format. Common confusions involve mixing columnar and row-oriented characteristics.

Answer

JSON: Columnar storage optimized for compression

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ORC: Row-oriented format with schema in each file

Question 7

Match each Azure service tier to its description.

Accepted Answer

Hot: Optimized for data that is accessed frequently and has low latency requirements.. In Azure Blob Storage and Data Lake Storage, access tiers are optimized for different access patterns. Hot is for frequent access, Cool for infrequent access (30 days), Cold for less frequent access (90 days), and Archive for rarely accessed data (180 days). Common confusions include swapping Cool and Cold descriptions or misattributing Archive characteristics.

Answer

Cool: Optimized for rarely accessed data stored for at least 180 days.

Answer

Hot: Optimized for infrequently accessed data stored for at least 30 days.

Question 8

Match each Azure monitoring service to its function.

Accepted Answer

Azure Monitor: Collects and analyzes telemetry from cloud and on-premises environments.. The correct matches are: Azure Monitor collects telemetry, Azure Log Analytics queries logs, Azure Application Insights monitors web apps, and Azure Service Health provides service health alerts. Common confusions occur between Azure Monitor and Application Insights, and between Azure Monitor and Log Analytics.

Answer

Azure Monitor: Monitors live web applications, detects anomalies, and analyzes performance.

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Azure Log Analytics: Collects and analyzes telemetry from cloud and on-premises environments.

Question 9

Match each data transformation concept to its definition.

Accepted Answer

PolyBase: A technology that allows querying external data sources like Hadoop or Azure Blob Storage using T-SQL.. The correct matches are: PolyBase queries external data via T-SQL; Data Lake is a raw data repository; ELT loads before transforming; Azure Data Factory is a cloud integration service. Common confusions include mixing up PolyBase with Data Lake, or ELT with Azure Data Factory.

Answer

PolyBase: A storage repository that holds a vast amount of raw data in its native format.

Answer

ELT: A cloud-based data integration service that orchestrates and automates data movement and transformation.

Question 10

Match each storage redundancy option to its description in Azure Storage.

Accepted Answer

LRS: Data is synchronously replicated three times within a single datacenter.. Common redundancies: LRS uses local replication, ZRS uses zonal replication, and GRS adds a secondary region. Distractors mix these concepts.

Answer

LRS: Data is replicated across multiple availability zones.

Answer

GRS: Data is replicated synchronously within a single datacenter.