Explanation:
https://docs.microsoft.com/en-us/azure/postgresql/overview-postgres-choose-server-options

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

Explanation:
https://docs.microsoft.com/en-us/azure/cosmos-db/create-graph-gremlin-console

To retrieve the product name, the correct SQL query will be:
SELECT c.productName FROM Items c
Option A is incorrect: db.Items.find({ },{productName:1,_id:0}) is a MongoDB query, not SQL.
Option B is correct: SELECT c.productName FROM Items c is the correct SQL command to retrieve the product name from the given JSON document Option C is incorrect: db.Items.find( {},{quantity:1,_id:0}) is a MongoDB query and we need to find the productName, not the quantity.
Option D is incorrect: SELECT c.unitCost FROM Items c is the SQL query but not correct. We need to retrieve the productName, not the unitCost.
Reference: To know more about the different queries and commands, refer to the link below:
https://docs.microsoft.com/en-us/learn/modules/choose-api-for-cosmos-db/2-identify-the- technology-options

Explanation:
Cutting cost of sales by at least 5 percent over the next two quarters requires prescriptive analysis to determine the actions you should take to meet that goal. This type of analysis is the goal of prescriptive analysis. Prescriptive analysis is used to help answer questions about what actions should be taken to achieve a goal or target Descriptive analysis would be used to see the correlation between advertising campaigns and recent orders. Descriptive analysis answers questions about what has happened based on historical data and can include complex relationships.
Predictive analysis would be used to determine when to rotate stock from summer to fall items.
Predictive analysis is used to help answer questions about the future by using historic data to identify trends.
None of the questions are based on a scenario in which you would use diagnostic analysis.
Diagnostic analysis looks into why things happen by identifying and analyzing data anomalies.
For example, you might use diagnostic analysis to investigate a sudden, unexpected increase in sales of camping equipment.