Section: Describe how to work with non-relational data on Azure
Explanation:
Time series data is a set of values organized by time. Time series databases typically collect large amounts of data in real time from a large number of sources. Updates are rare, and deletes are often done as bulk operations. Although the records written to a time-series database are generally small, there are often a large number of records, and total data size can grow rapidly.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/guide/technology-choices/data-store-overview

Section: Describe an analytics workload on Azure
Explanation:
B: Transactional data tends to be heavy writes, moderate reads.
D: Typical traits of transactional data include: schema on write, strongly enforced F: Transactional data tends to be highly normalized.
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/online-transaction-processing

Reference:
https://docs.microsoft.com/en-us/power-bi/connect-data/service-datasets-across-workspaces
https://docs.microsoft.com/en-us/power-bi/consumer/end-user-dashboardshttps://powerbi.microsoft.com/en-us/excel-and-power-bi/

Azure Storage offers two options for copying your data to a secondary region:


With GRS or GZRS, the data in the secondary region isn't available for read or write access unless there is a failover to the secondary region. For read access to the secondary region, configure your storage account to use read-access geo-redundant storage (RA-GRS) or read-access geo-zone-redundant storage (RA-GZRS).
Reference:
https://docs.microsoft.com/en-us/azure/storage/common/storage-redundancy#redundancy-in-a-secondary-region