One of the buzzwords in the IT world
apart from cloud computing technology is big data. For a lot of people, (the concept) is hard to comprehend
because no matter the size of the data, data has been around us all the time.
Why now in a sudden, big data becomes significant and gathers so much attention?
And how big is one’s data to be considered as BIG data?
 |
| Big Data |
Big data is claimed to be valuable
in improving service and user experience, and sometimes, even to refine prediction. So, as a not-so-big company, what is
the size of data we have? If it can be considered as big data, how can we make
use of it? I pondered a little and told the cloud surveillance development team
on how we can tap on big data to improve our service.
Currently, we are using a customer's
last page view as default for their next login page. This is hoped to reduce
the unnecessary clicking and to bring the customer straight to the
"intended" page. We went ahead with this decision only based on the assumption
that customers would always want to visit their last logout page the next time
they login. However, this built-in
mechanism may not be necessarily right even when we observed a high hit rate on
the relevant pages.
Hence, I suggested
that they crunch individual customer’s data for a period of one month
based on two parameters, frequency of page log and total time spent on a page, and
strike a balance between the two. Therefore,
if a customer’s behavior changes, the intended first view page would also change
accordingly to improve user experience. The method is considered a deployment
of the big data concept on a smaller scale.
 |
| Big Data |
According
to Viktor Mayer-Schönberger and Kenneth Cukier in their book, Big Data,
“Data was no longer regarded as static or
stale, whose usefulness was finished once the purpose for which it was
collected was achieved, such as after the plane landed (or in Google’s case,
once a search query had been processed). Rather, data became a raw material of
business, a vital economic input, used to create a new form of economic value.
In fact, with the right mindset, data can be cleverly reused to become a
fountain of innovation and new services. The data can reveal secrets to those
with humility, the willingness, and the tools to listen.”
In the
past we depended on samplings when dealing with large populations and numbers.
This was due to the constraints of tools to collect, organize, store and
analyze data, which often times did not provide enough confidence to the
participants and led to many cases of self-censorship. But with the era of big
data, where N=all, using all the available data lets us see details we never
could when we were limited to smaller quantity of data.
When we
can make use of data effectively, some market surveys become irrelevant because
now you realize that the answers to your questions are somehow buried deep down
somewhere in the pool of your big data, something that you possess all these
while. If you know how to excavate the dormant value, it’d give you much
accurate findings than those sophisticated pricey market surveys.
 |
| Big Data |
For
example, when you dine in a restaurant, a waitress approached you with the
sweetest smile she could muster and passed you a survey form to fill. If the
service column were filled with “excellent”, she would have a chance for a pay
hike. In such a case, you would oblige hoping that your response helps her to
get a raise.
In a market survey however, we usually tend to ask why in our effort to understand the preference of our customers. But when we’re dealing with big dataset, it’s more towards what, rather than why. The big data tells you outright about what is happening, and what you should do next.
That’s how
the Internet giants, Google, Amazon
and Facebook become humongous and
invincible. For them to improve their services in all aspects; they dig into
their own data, find the logic, extract the hidden value, and act according to pattern
of the data. With astronomical quantity of data, the numbers speak for
themselves, without any need of conceptual model and hypothesis.
Big data
marks the beginning of a major transformation, from quantitative to qualitative
change. Since we are providing two cloud services,
TimeTec as a cloud based workforce management system and IPCamera as cloud
surveillance system; we will start to collect data in a larger scale. How can
we differentiate ourselves among the competitors? This relies on how data
holders open up their big-data mindset, continuously improve the algorithms,
innovate the services and enhance user experience too.
When
words, locations and interactions are considered data; when one can dataficate
almost everything; the big data race is on. The earlier a web firm can capture
and reuse its data, the accumulative of data exhaust would turn into a huge
competitive advantage for the company, and raises the barrier of entry against its
rivals.
