Mixed Deck — All DP-200 Topics Flashcards

What is the purpose of a linked service in Azure Data Factory?

Answer: To store connection information for a data store or compute resource

A linked service in ADF defines the connection string and credentials needed to connect to an external data store or compute target.

You have an Azure Data Factory pipeline that loads source data into an Azure Data Lake Storage Gen2 account incrementally. The source table's LastUpdatedDate column identifies the data to be loaded. Every four hours, you intend to run the pipeline. You must make certain that the pipeline's execution fits the following criteria: When a pipeline run fails owing to concurrency or throttling constraints, the execution is automatically retried. Backfilling existing data in the table is supported. What kind of trigger should you employ?

Answer: tumbling window

A tumbling window trigger is ideal for this scenario because it fires at a fixed time interval (every four hours) and creates non-overlapping, contiguous windows. This trigger type inherently supports automatic retries for failed executions and allows for easy backfilling of existing data by re-running specific past windows. These features ensure robust and manageable incremental data loading.

You're working on an Azure Data Lake Storage Gen 2 application. You must propose a method for granting permissions to a certain application for a set length of time. What should your advice include?

Answer: shared access signatures (SAS)

Shared Access Signatures (SAS) are the recommended method for granting time-limited and granular permissions to specific resources in Azure Data Lake Storage Gen2. A SAS token provides delegated access to storage resources for a specified period, with defined permissions and an optional IP address restriction. This ensures that the application only has the necessary access for a controlled duration, enhancing security.

What is the purpose of result-set caching in Azure Synapse Analytics dedicated SQL pool?

Answer: To return cached results for repeated identical queries without re-executing the computation

Result-set caching stores the output of a query and serves the same result for subsequent identical queries, dramatically reducing latency for repeated BI queries.

Which Cosmos DB consistency level provides the strongest consistency guarantees?

Answer: Strong

Strong consistency guarantees that reads always return the most recent committed write, at the cost of higher latency.

In Azure SQL Database, what is the purpose of Query Store?

Answer: To capture query execution plans and runtime statistics for performance troubleshooting

Query Store persists query execution plans, runtime statistics, and wait statistics over time, enabling analysis of query performance regressions.

What is the purpose of Streaming Units (SUs) in Azure Stream Analytics?

Answer: They represent the compute resources (CPU and memory) allocated to a Stream Analytics job

Streaming Units represent the combined CPU and memory resources allocated to a Stream Analytics job, and scaling SUs increases processing throughput.

Which output sink in Azure Stream Analytics is best suited for storing aggregated results in a relational format for BI reporting?

Answer: Azure SQL Database

Azure SQL Database is the ideal relational output for Stream Analytics aggregations that will be consumed by BI tools like Power BI.

You're keeping an eye on an Azure Stream Analytics job. For the last hour, the number of Backlogged Input Events has been 20. The number of Backlogged Input Events must be reduced. What are your options?

Answer: Increase the streaming units for the job

A persistent number of backlogged input events in an Azure Stream Analytics job indicates that the job's processing capacity is insufficient to handle the incoming data volume. To reduce this backlog and allow the job to catch up, you should increase the streaming units (SUs) allocated to the job. Streaming units represent the computing resources, and more SUs provide greater throughput and processing power.

Which Azure feature allows you to classify and label sensitive data in Azure SQL Database and Azure Synapse Analytics?

Answer: Data Discovery & Classification

Data Discovery & Classification scans databases to identify, label, and report on columns containing sensitive data like PII or financial information.

Which Azure service is best suited for orchestrating complex data workflows that include both batch and real-time components with dependencies between steps?

Answer: Azure Data Factory

Azure Data Factory is a cloud-scale data integration service that orchestrates both batch ETL and hybrid data pipelines with rich dependency and scheduling capabilities.

What is the purpose of Azure Private Endpoint for Azure Storage?

Answer: To provide a private IP within your VNet for secure access to storage without traversing the public internet

A Private Endpoint assigns a private IP address within your VNet to a storage account, ensuring traffic never leaves the Microsoft backbone network.

Pool1 is an Azure Synapse Analytics dedicated SQL pool, and DB1 is a database. Table1 is a fact table found in DB1. In Table1, you must determine the amount of the data skew. In Synapse Studio, what should you do?

Answer: Connect to Pool! and query sys.dm_pdw_nodes_db_partition_stats

To determine data skew in an Azure Synapse Analytics dedicated SQL pool, you should connect to the dedicated SQL pool (Pool1) and query the `sys.dm_pdw_nodes_db_partition_stats` Dynamic Management View (DMV). This DMV provides detailed information about data distribution across the compute nodes, including row counts per partition, which is crucial for identifying uneven data distribution or skew. Data skew can significantly impact query performance in a distributed system like Synapse.

In Azure Synapse Analytics, what is a PolyBase external table used for?

Answer: Querying data stored outside Synapse such as ADLS Gen2 without importing it

PolyBase external tables allow Synapse Analytics to query data stored in external sources like ADLS Gen2 or Azure Blob Storage without moving it.

Which Azure service is the managed platform for running Apache Spark and Apache Hadoop clusters for large-scale batch processing?

Answer: Azure HDInsight

Azure HDInsight is Microsoft's fully managed cloud distribution of open-source frameworks including Hadoop, Spark, Kafka, and HBase.

Which Azure HDInsight cluster type is optimized for real-time stream processing and message queuing?

Answer: Kafka

HDInsight Kafka provides a managed Apache Kafka cluster optimized for high-throughput, fault-tolerant real-time message streaming.

What is the shared responsibility model implication for data security in Azure PaaS data services like Azure SQL Database?

Answer: Microsoft manages infrastructure security; the customer is responsible for data classification, access control, and encryption configuration

In PaaS, Microsoft handles infrastructure, physical security, and OS patching, while customers retain responsibility for data governance, access policies, and encryption choices.

What is the primary function of the Copy Activity in Azure Data Factory?

Answer: To move data from a source data store to a destination data store

Copy Activity in Azure Data Factory is optimized for data movement, copying data from a supported source data store to a sink (destination) data store.

What is the primary purpose of Azure Event Hubs Capture?

Answer: To automatically archive streaming events to Azure Blob Storage or ADLS Gen2 for batch analysis

Event Hubs Capture automatically stores the full stream of events to Azure Blob Storage or ADLS Gen2 in Avro format for downstream batch processing.

In Azure Data Factory, which construct is a logical grouping of activities that together perform a unit of work?

Answer: Pipeline

A Pipeline in Azure Data Factory is a logical grouping of activities—such as Copy, Data Flow, and stored procedure activities—that together accomplish a data integration task.