D.

READ_COMMITTED_SNAPSHOT to ON

In SQL Server, you can also minimize locking contention while protecting transactions from
dirty reads of uncommitted data modifications using either:
The READ COMMITTED isolation level with the
READ_COMMITTED_SNAPSHOT database option set to ON.

Explanation:-

The SNAPSHOT isolation level.
If READ_COMMITTED_SNAPSHOT is set to ON (the default on SQL Azure Database),
the Database Engine uses row versioning to present each statement with a transactionally
consistent snapshot of the data as it existed at the start of the statement. Locks are not
used to protect the data from updates by other transactions.
Reference:
https://docs.microsoft.com/en-us/sql/t-sql/statements/set-transaction-isolation-leveltransact-
sql

B.

Microsoft.EventGrid

Event-driven architecture (EDA) is a common data integration pattern that involves
production, detection, consumption, and reaction to events. Data integration scenarios
often require Data Factory customers to trigger
pipelines based on events happening in storage account, such as the arrival or deletion of a file in Azure Blob Storage account. Data Factory natively integrates with Azure Event
Grid, which lets you trigger pipelines on such events.
Reference:
https://docs.microsoft.com/en-us/azure/data-factory/how-to-create-event-trigger

C.

Azure HDInsight

Explanation:
Azure HDInsight offers pre-made, monitoring dashboards in the form of solutions that can
be used to monitor the workloads running on your clusters. There are solutions for Apache
Spark, Hadoop, Apache Kafka, live long and process (LLAP), Apache HBase, and Apache
Storm available in the Azure Marketplace.
Note: With Azure HDInsight you can set up Azure Monitor alerts that will trigger when the
value of a metric or the results of a query meet certain conditions. You can condition on a
query returning a record with a value that is greater than or less than a certain threshold, or
even on the number of results returned by a query. For example, you could create an alert
to send an email if a Spark job fails or if a Kafka disk usage becomes over 90 percent full.
Reference:
https://azure.microsoft.com/en-us/blog/monitoring-on-azure-hdinsight-part-4-workloadmetrics-
and-logs/

A.

Transparent Data Encryption (TDE)

Explanation:
Transparent data encryption (TDE) helps protect Azure SQL Database, Azure SQL
Managed Instance, and Azure Synapse Analytics against the threat of malicious offline
activity by encrypting data at rest.

Table
Description automatically generated with low confidence

B.

%

Explanation:
Explanation/Reference:
You can override the default language by specifying the language magic command
% at the beginning of a cell. The supported magic commands are: %python,
%r, %scala, and %sql.
Reference:
https://docs.microsoft.com/en-us/azure/databricks/notebooks/notebooks-use