Introduction to Streaming Data - Real-Time Analytics - page 3

Chapter 11. Google seems to be especially interested in a technique called
deep learning, which makes use of very large-scale neural networks to learn
complicated patterns.
These systems are even enabling entirely new areas of data collection and
analysis by making the Internet of Things and other highly distributed data
collection efforts economically feasible. It is hoped that outlining some of
the previous application areas provides some inspiration for
as-of-yet-unforeseen applications of these technologies.
Operational Monitoring
Operational monitoring of physical systems was the original application
of streaming data. Originally, this would have been implemented using
specialized hardware and software (or even analog and mechanical systems
in the pre-computer era). The most common use case today of operational
monitoring is tracking the performance of the physical systems that power
the Internet.
These datacenters house thousands—possibly even tens of thousands—of
discrete computer systems. All of these systems continuously record data
about their physical state from the temperature of the processor, to the
speed of the fan and the voltage draw of their power supplies. They also
record information about the state of their disk drives and fundamental
metrics of their operation, such as processor load, network activity, and
storage access times.
To make the monitoring of all of these systems possible and to identify
problems,thisdataiscollectedandaggregatedinrealtimethroughavariety
of mechanisms. The first systems tended to be specialized ad hoc
mechanisms, but when these sorts of techniques started applying to other
areas, theystartedusingthesamecollection systemsasotherdatacollection
mechanisms.
Web Analytics
The introduction of the commercial web, through e-commerce and online
advertising,ledtotheneedtotrackactivityonawebsite.Likethecirculation
numbers of a newspaper, the number of unique visitors who see a website
in a day is important information. For e-commerce sites, the data is less