Final answer:
Dashboards that monitor continuous incoming information analyze streaming data. This data is distinct from categorical, qualitative, and discrete data in that it flows continuously and includes various forms of live and real-time data.
Step-by-step explanation:
In data analytics, dashboards that monitor data from a continuous source of incoming information are dealing with streaming data. This term describes data that is generated continuously by numerous data sources, which typically send data records simultaneously and in small sizes (often in kilobytes). Streaming data includes a wide variety of data, such as logs from web applications, telemetry from IoT devices, and live feeds from social media or financial trading applications. Unlike categorical data or qualitative data, which typically refer to data that can be categorized based on names or labels, streaming data is characterized by its continuous flow.
Similarly, streaming data is distinct from discrete data, which represents counts or numbers that can take on only specific values, often with gaps in between. As for other types of data referenced, quantitative discrete data would be data that can be counted and has a finite number of possible values, such as the number of times per week something occurs. Quantitative continuous data, on the other hand, would be data that can take on any value within a given range, like a duration of time. In data analytics, dashboards monitor data that is a continuous source of incoming information. The type of data that describes this continuous source of incoming information is called streaming data (option D). Here, data is continuously generated and updated in real-time, such as live sensor data, social media feeds, or stock market prices.