SMU_AMI_November_Spread

Vol.2 / Asian Management Insights
A digital genome, or
profile of any person
or object, is created
through algorithms that
encode hundreds of
traits or characteristics
of a person or object.
Structured versus
unstructured data:
New techniques and
vast opportunities
The data that we receive today is either
structured or unstructured—structured
data are those coming from transactions
while unstructured data are generated
from social media platforms and other
websites. The majority of the world’s data
is structured, meaning that it appears in
rows and columns and can be labelled. In
recent times, however, there has been a
rapid growth in unstructured, unlabelled
data in the form of blogs, posts, texts,
tweets, images, audios and videos.
While it is easy to recognise and
interpret structured data, the same does
not hold true for unstructured data.
Unstructured data comes in many varieties
such as images, video, audio, languages,
and locations from GPS, iBeacon, WiFi
and mobile networks. New technologies
such as object and facial recognition,
emotion detection, as well as advanced
methods of classification are required
to understand images and videos. There
are similar issues with audio files where
modern voice and language recognition
along with inflection detection are needed
to analyse sounds.
Converting unstructured data into
structured and searchable forms is just the
beginning of the problem for computers
and analysts. The power of Big Data lies
in the ability to collate, compare, analyse
and interpret this rapidly accumulating
heterogeneous volume of data to reveal
trends and patterns so that it can be
used in decision-making. The question
then arises: Are there technologies that
can help us?
Even until just a few years ago, we
did not have the capability to efficiently
and affordably isolate patterns and
fashion data to fit a company’s processes
and audience. Owing to strides in
technological innovation, some
advanced Big Data platforms are now
equipped with features that allow them
to draw inferences that extrapolate from
the gathered information. Big Data
technology allows companies to
analyse images and manipulate them
to deliver a differentiated customer
experience. For instance, Ikea allows
its customers to download a mobile
app that takes pictures of its products
like furniture, and virtually position
them in their living room as augmented
reality. Simply put, these platforms do
some of the thinking for you.
Digging for digital gold
I like to compare Big Data analytics to
gold mining. We have a rich seam of gold
deposits and we need to cut through
the rocks and boulders and sieve
What makes
Big Data
Big Data is a term used to
describe the availability
of massive amounts of
structured and unstructured
data generated through
business and social
interactions. The ‘three Vs’
that make data ‘big’ are:
‘big’?
Volume
The sheer volume of data
being generated today
challenges businesses
to determine its relevance
and how to analyse it.
The Internet has been a
single most important
contributing factor to this
trend.
Velocity
Data is streaming in at
unprecedented speed
through multiple channels,
with the total quantity of
accessible data doubling
every one and a half years.
This triggers the need for
businesses to react
quickly to deal with bulks
of incoming information
in real time.
Variety
Data can be found in
a variety of forms—
documents, audio, video,
e-mail, financial transactions,
and social media, among
others. This poses the
difficulty of comparing apples
with oranges, and businesses
are faced with the challenge
of collating, governing and
merging the various types
of data to be analysed
and interpreted.
Source: SAS, “Big data: What it is and why it matters”