A company needs to optimize data storage costs in Azure. Which strategy should they prioritize?
AUse Azure Data Lake Store
BImplement data lifecycle management
CMaximize redundant storage options
DIncrease storage throughput
Explanation
Implementing data lifecycle management helps reduce costs through automated tiering or deletion, while others can increase expenses.
Q102
You are configuring data movement with Azure Data Factory. What happens when you set a fault tolerance option for data copies?
AStops on the first failure
BRetries until successful or timeout
CLogs errors only
DSkips invalid records silently
Explanation
Setting fault tolerance allows for retries to ensure data reliability, whereas other options either ignore or lack persistence in error handling.
Q103
Which service helps manage and analyze data in real time?
AAzure Stream Analytics
BAzure SQL Database
CAzure Blob Storage
DAzure Data Factory
Explanation
Azure Stream Analytics is designed for real-time data consumption; others focus on different data management aspects.
Q104
A company wants to ingest large data sets efficiently into Azure Data Lake. What is the best option to achieve this?
AAzure Functions
BAzure Data Lake Storage Gen2
CAzure Blob Storage
DAzure SQL Database
Explanation
Azure Data Lake Storage Gen2 specializes in managing large datasets; other options are not optimized for such ingestion.
Q105
You are configuring Azure Synapse Analytics. What happens when you define a table with CLUSTERED columnstore?
AIt boosts write performance.
BIt helps in data compression.
CIt uses row-based storage.
DIt disables data partitioning.
Explanation
CLUSTERED columnstore enhances data compression; other options reflect misconceptions about performance or storage type.
Q106
Which service is best for real-time analytics on streaming data?
AAzure Stream Analytics
BAzure Data Factory
CAzure Blob Storage
DAzure SQL Database
Explanation
Azure Stream Analytics specializes in real-time processing, while the others focus on storage or batch processing.
Q107
A company needs to efficiently manage large volumes of diverse data. Which design principle should they consider?
AData Redundancy
BDatabase Sharding
CData Monolith
DData Silos
Explanation
Database sharding helps scale and manage large datasets, whereas the other options lead to inefficiencies or increased complexity.
Q108
What happens when an Azure Data Lake is configured without access controls?
AOnly admins can access data
BAll users can access data
CData is automatically encrypted
DConnections are terminated immediately
Explanation
Without access controls, the default behavior is open access to all, while the others do not reflect real access conditions.
Q109
Which service is best for real-time analytics on streaming data in Azure?
AAzure Stream Analytics
BAzure Blob Storage
CAzure Synapse Analytics
DAzure Data Factory
Explanation
Azure Stream Analytics is designed for real-time analytics on streaming data, while the others serve different purposes.
Q110
A company needs to transform and move data into a data lake nightly. Which service do you recommend?
AAzure Logic Apps
BAzure Data Factory
CAzure Data Lake Storage
DAzure Functions
Explanation
Azure Data Factory is best suited for orchestration of data movement and transformation workflows, unlike the other options.