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36 Big Data Analytics for Connected Vehicles and Smart Cities What Is Big Data? 37

I’ll contrast these numbers to an experience at the London Borough of
Hackney in the early 1980s when a Superbrain personal computer with a 2-Mb
hard disk was acquired. Staff and management were not sure what they were
going to do with all that storage space! Note that a megabyte is a billionth of a
petabyte.

Velocity
It would be simple to equate the velocity at which data arrives as the number
of bits per second that a telecommunications link can support. For example, a
typical Internet connection for business might support data speeds of around
100 Mbps. However, the velocity dimension goes beyond the speed at which
communications can be achieved to address a wider measurement of the speed
at which we can go from sensing data to doing something about it. While data
communications throughput and latency can measure the speed at which data
can flow across the network, there are other factors that will influence the speed
at which we can make use of the data and turn it into information. As shown in
Figure 3.3, there are several steps in this process, addressed as follows.

• Sense: In this step the data is collected by several different means in-
cluding sensors, closed-circuit TV cameras, smart phones, and roadside
infrastructure-based sensors. The data can also include anecdotal data
and can be structured or unstructured.
• Ingest: This is the process step in which the data is assembled into a data
platform and brought together into a meaningful and coherent body of
data. This topic is discussed in Chapter 9.
• Process: In this step the raw data is turned into information. The huge
volume of zeros and ones and raw signal data is converted into meaning-
ful summaries, tables, visualizations, and other such structures that allow
humans to understand the trends and patterns within the data.
• Assimilate: In this step of the process, the humans involved assimilate the
information and begin to think about the impact that the information
will have on their job and their organizations. This may well lead to the
recognition that further information is required. It may also highlight
the need for organizational fine-tuning to ensure that the assimilation
process is as efficient as it can be.

Figure 3.3 Steps from sensing to action.