Recent technology trends shows that Big Data is one the
emerging trends that is picking up fast across the organizations. It helps in
unlocking the huge potential hidden underlying the huge set of information spread
around us in different formats and types. And there are lot many articles
already shared about what and how Big Data can be used in various industry
scenarios. In this article, we try to add a totally new dimension to the Big
Data thinking….a Multilingual Big Data.
Imagine a scenario, any international level enterprise – say
some travel agency, or some hospital, or any international food chain, or some
international retail chain having its presence across multiple continents
across the globe. They need to daily deal with local people residing in the
respective areas, and often need high level of interaction with those local
people for churning out a good business. As reflected in a well-known quote
from Nelson Mandela, communicating in native languages makes the easiest way to
establish trust among the people.
“If you talk to a man in a language he understands, that
goes to his head. If you talk to him in his language, that goes to his heart.” ~Nelson Mandela[1]
The enterprises can hire local people for all the verbal
communications, but then there is equal amount of written communication
(tickets, bills, instructions, instructions etc.) required for almost each step
of interaction.
Now imagine having robust IT Systems for supporting for
these native languages, so as to manage and maintain all the native
communications as-is in digital formats. And not just keep the digital records,
but also leveraging this digital data directly for critical business elements
like business analysis and marketing strategy development etc. Ability to
leverage the support for native languages can result into miraculous results in
many ways. Let us take an example of the second most spoken language in the
world to understand the situation better.
An example of Multi-Lingual Bigger Data - Hindi:
Hindi language is the second most spoken language in the
world after Mandarin Chinese[2].
Indian songs and hymns have been adapted and used by various popular rap and
pop music artists. From science to commerce and business to various multimedia
as shown India to becoming a viable world economy with increasing interest in
the world.
Recent study by global firms also mentions that many Top
global IT firms have more staff in India than home nations.[3]
This fact is enough to suggest that almost every big enterprise is now willing
to have presence in India. With having a such a huge workforce working for all
major enterprises of the world, just image the way things could be turned
around by putting an integrated system for taking inputs in their local
language (most prominent of which is Hindi), doing analysis of that data within
its native format, and then producing outcome analysis and reports directly in
the same language. Employees getting training in their local languages, using
Hindi language take feedback from end customers, and leveraging them directly
into analytical purposes. Information available on page-scans written in local
languages can directly go into systems. Preparing product collaterals (like
user manuals), or doing analysis (sentiment analysis) could become so faster if
data can be leveraged directly from source into the advanced IT systems. Instructions
can be generated in native languages, so that every local native can understand
them. This can just accelerate the rate at which entire business cycle moves.
Other benefactors:
Ability to leverage the support for native languages can
result into miraculous results not only for the enterprises, but also for the
local agencies like Government departments, small and medium industries, where
mostly local people are both the employees and the end users. Entire
departments running on their local languages would be able to take advantage of
the faster processing and analytical
capabilities of such advanced technology concepts…known as big data, and
targeting to (soon or later) become a
Bigger Data.
