Explanation

All cloud data must be encrypted at rest and in transit.
Box 1: Transparent data encryption
Encryption of the database file is performed at the page level. The pages in an encrypted database are encrypted before they are written to disk and decrypted when read into memory.
Box 2: Encryption at rest
Encryption at Rest is the encoding (encryption) of data when it is persisted.
References:
https://docs.microsoft.com/en-us/sql/relational-databases/security/encryption/transparent-data-encryption?view=
https://docs.microsoft.com/en-us/azure/security/azure-security-encryption-atrest

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-workload-metrics-and-logs/

Explanation
In Azure, all of the following data stores will meet the core requirements supporting real-time processing:
* Apache Spark in Azure Databricks
* Azure Stream Analytics
* HDInsight with Spark Streaming
* HDInsight with Storm
* Azure Functions
* Azure App Service WebJobs
Note: Lambda architectures use batch-processing, stream-processing, and a serving layer to minimize the latency involved in querying big data.

Reference:
https://azure.microsoft.com/en-us/blog/lambda-architecture-using-azure-cosmosdb-faster-performance-low-tco-l
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/stream-processing
https://docs.microsoft.com/en-us/azure/cosmos-db/lambda-architecture

Auditing has been enhanced to log sensitivity classifications or labels of the actual data that were returned by the query. This would enable you to gain insights on who is accessing sensitive data.
Note: You now have multiple options for configuring where audit logs will be written. You can write logs to an Azure storage account, to a Log Analytics workspace for consumption by Azure Monitor logs, or to event hub for consumption using event hub. You can configure any combination of these options, and audit logs will be written to each.
Reference:
https://azure.microsoft.com/en-us/blog/announcing-public-preview-of-data-discovery-classification-for-microsoft-azure-sql-data-warehouse/

Explanation

Box 1: Cosmos DB indexes
The report for Backtrack must execute as quickly as possible.
You can override the default indexing policy on an Azure Cosmos container, this could be useful if you want to tune the indexing precision to improve the query performance or to reduce the consumed storage.
Box 2: Cosmos DB TTL
This solution reports on all data related to a specific vehicle license plate. The report must use data from the SensorData collection. Users must be able to filter vehicle data in the following ways:
* vehicles on a specific road
* vehicles driving above the speed limit
Note: With Time to Live or TTL, Azure Cosmos DB provides the ability to delete items automatically from a container after a certain time period. By default, you can set time to live at the container level and override the value on a per-item basis. After you set the TTL at a container or at an item level, Azure Cosmos DB will automatically remove these items after the time period, since the time they were last modified.