In Broadcast - CABSAT 2015 - 11


11

www.inbroadcast.com | CABSAT InShow Guide | 10-12 March 2015

Exploring The Ocean
Of T&M Data
By Simen Frostad,
Chairman

I

t has been said that knowledge is like
a pool of light: the larger it is, the
greater the circumference of darkness
that surrounds it. Or, the more we
know, the more we discover new things
we don't know. Then, as someone else
put it, there are the known unknowns,
and the unknown unknowns. We are
aware of the darkness at the edge
of the pool of light, but not what lies
further in the shadows behind the edge.
So our exploration of the unknown
almost always proceeds in a way
that is defined by what we already
know. Only occasionally does a flash
of intuition descend on a scientist
or inventor, so that some new way
of thinking emerges, and with it the
freedom to find new knowledge. Some
of the most important advances in
science have occurred this way.
But empirical testing has been the
cornerstone of scientific thought for
centuries, and even the most breathtaking intuitive leap must be tested
against existing understanding of
reality if it is to be proved and become
accepted 'knowledge'. Science exists
therefore in a balance or dialectic
between the imagination of the
scientist, and empirical testing to
determine whether or not the theory
is valid.
In the world of test and monitoring

for digital media, the conventional
model is heavily weighted towards
the empirical. The industry uses T&M
technology to watch and test our
systems, and we respond to the alarms
when things go wrong. We use defined
criteria to observe the functioning of
the systems within set parameters,
and when a variable strays outside
those parameters, the T&M equipment
alerts us. Many people consider this
to be the only thing we should expect
from test and monitoring.
A thermometer works in a similar
way: it tests for a single defined
criterion, and we may use this simple
test to observe when acceptable
parameters have been attained. But if
we want to go beyond simply knowing
that today at 12:00 it is hotter than it
was yesterday at the same time, we
need to consider other parameters.
We need to put one test in the context
of others, because temperature alone
only tells us 'what is', but if we want to
understand 'what will be', and 'why',
we must have much more nuanced and
correlated information.
Even a basic weather forecast
takes into account many factors and
sources of information, including air
pressure and movement, land and sea
temperatures at multiple locations,
ocean currents, the development of

Correlating data from multiple sources gives insight into new patterns

Virtual video walls can be configured to show any combination of monitoring data

weather systems in other parts of the
globe that will influence the systems in
our own area, and so on. With all this
information to hand, the meteorologist
can analyse conditions based on
known precedent, and begin to predict
what should happen in the short term.
For a long range forecast and the
prediction of larger trends in global
weather systems, advanced computer
modelling systems are required. The
knowledge gained from this kind of
modelling helps us decide how we
should plan for eventualities such as
rising sea levels, increased energy
demands, and regional famine.
The current T&M model is more akin
to the thermometer hung outside the
front door than to long-range weather
modelling technology. This is a pity,
because an advanced T&M system can
gather and correlate an inconceivably
huge amount of data, and if the system
only applies simple thermometertype tests to this information, a great

opportunity is being lost to understand
and predict the future.
In the connected media consumption
landscape, there is a vast amount of
data to be accessed and understood by
the digital media operator. Every OTT
client and set-top box can contribute
to a rich data resource for the operator
to use in identifying and understanding
new patterns of use, emerging market
niches, increased competitive stress,
and so on. But the enormous volumes
of data available need exceptional
analysis tools if the data is to make
sense.
Complex scientific research makes
use of advanced visualisation to pick
a path through massive data sets,
with the ability to correlate data
from heterogeneous sources as a
way of discovering new patterns and
connections. Advanced visualisation
can do something similar in our
industry.
What's needed is the ability to
use this treasure house of data in
innovative ways, so that it can be
sliced and visualised from any angle,
with correlations from multiple
sources both inside and outside the
T&M system, and with the capacity to
use the data for predictive modelling.
In other words, instead of the current
rather flat-earth T&M model, which is
tilted towards reporting on what we
already know, the industry should be
demanding a model that allows us to
explore what we don't know, and to
hypothesise using the data the system
gathers. Instead of being confined to
showing a red light when a problem
has already occurred, advanced T&M
can become a tool for navigating an
ocean of information, identifying
hazards looming on the horizon, and
striking out for opportunities and
profitable new destinations beyond.


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http://www.nxtbook.com/nxteu/lesommet/inbroadcast_cabsat2015
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