Big Data and Analytics Summit 2014 – NASSCOM
When: 27th
June 2014, 9:00 AM – 5:15 PM
Where: Hotel
Trident, Hyderabad
Sponsored By: Accenture,
CapGemini, Paypal, Airtel, EXL, Virtusa, Genpact, Contact Singapore, Target
Highlights:
1.
The Nasscom event was attended by thousands of
analysts, architects, data scientists and managers across India. It provided a
platform to interact with the market leaders like Mu Sigma, Amazon, P&G,
Target, Paypal, Indix, Simplify360 and many more. It was a full day event with
lots of presentations, tech talks, panel discussions, Q&A sessions, and
product demos.
2.
There were many stalls at the event. For instance, at the Accenture stall were two
products exhibited – one was for automobile insurance the other one was for
video analytics using Google glass. A car will be fitted with sensors that
measure the speed, friction, wear and tear of the vehicle. These recordings are
used to calculate the risk in real-time. Insurance premium is determined by the
risk; for a safely driven car the premium is lower.
3.
Marc Chemin from CapGemini spoke about the
advent of Big Data in Europe.
·
Big data is used in 3 areas – enhancement (e.g.
to boost sales), disruption & new business.
·
With the advent of Big Data and Analytics, a lot
of Public agencies are being replaced by Private agencies. The public agencies
work in silos and don’t usually share any public data. However very intelligent
systems can be built by sharing data, and winning people’s confidence.
·
Lastly it was discussion around Data privacy in
Europe. There are 29 authorities in Europe and each of them defines their own
privacy policies around data regulation. Hence it gets tough to execute some of
the Big Data projects.
4.
Michael Barnes from Forrester Research provided
a lot of insights to Analytics market.
·
In the earlier days data was used as a system of
record, now it is used as system of engagement to touch people. More and more
companies are coming out and investing in Business Technologies to provide
better customer experience.
·
In the earlier days data was scarce, expensive,
easy to manage, neat-rich-structured, manageable number of formats and
structures. With Big data we have plenty of data, cheap, impossible to manage,
messy & detailed, nearly infinite in format & structure.
·
Getting the right & sufficient data, skills,
technology and experience are key requirements to work in Analytics.
·
Currently Big Data is used for real-time
reporting. In future it will be used for process automation, adhoc decision
support, operational planning, and strategy planning.
·
Michael gave this wonderful definition – “Big
Data is not a technology, a project, an objective with a single compute. It is
a journey, process, strategic effect. The practices & technologies that
close the gap between the data available and able to turn data into business
insights”.
5.
This was followed by presentation by Michael
Svilar from Accenture Analytics. Some of the projects that they are executing –
Connected Cars, Network Analytics, Safe City & Smart Water (to stop wastage
of water in UK using Big Data). The statistics shows that in India 94% of the
companies that use Big Data are satisfied with the results. Out of this, 65%
are using to analyze customer behavior.
6.
The real crowd puller was by Dheeraj Rajaram,
founder of one of the most successful startup in Analytics – Mu Sigma. He
discussed some of the innovations in Analytics.
·
Innovation 1 – How some of the companies are
using Social Score to sanction loans. They analyze how people are spending on
and on what they are spending, by analyzing their Facebook posts.
·
Innovation 2 – Real-time video analytics used to
determine possibility of fraud in betting industry.
·
Innovation 3 – Field engineers constantly face
the risk of their lives. Big Data is being used to put an end to this. By 2015,
6 Billion devices will be connected.
7.
The next session was on Fraud Detection &
Risk Management in online and offline space.
·
Online ecommerce companies constantly face the
issue of Fraud & Risk (Cash On Delivery - customer might not pay for the
item). Money-back guarantee is another big blow for these companies with the
U.S dealing with 2.3 b$ worth of returns annually. Amazon quoted about this
issue saying, companies need to be customer centric and always start with the
customer in mind & work backwards. Consider a scenario where a lady
purchases a lot of baby accessories and while billing she forgot to bill a baby
wipe which was at the bottom of the basket. Instead of treating it as a theft,
the store can be polite in asking her if she would like to bill anything else.
·
In the online space when a customer makes a
purchase, all that the company has to predict risk is 50 milli second. In an
offline mode user has an identity. However in the online mode, all that the company
knows is the customer’s email id. Within 50 ms, 1000s of rules and predictive
models have to be executed and validated.
·
In the online space even a tiniest loophole can
be disastrous in lightning viral environment. So companies cannot create any
space for mistake.
·
Do not just rely on a supervised learning method
for your business. You would need unsupervised learning, random forest, neural
networks, decision trees and many more.
·
One instance of fraud was discussed by the
panel. There were 20 banks in Somalia and in a span of few weeks, 15 of the
banks were mugged. The Somalia government approached the analysts to predict
when the remaining 5 banks will be mugged, using statistical analysis.
8.
The panel discussion by the startups was the most
motivating of all the talks. Bhupendra from Simplify360 & Sridhar Venkatesh
from Indix kept the whole crowd on the toes. They spoke about their journey
from nowhere to becoming the most promising startup. Bhupendra shared his experiences of starting
a product with no roadmap in 2009, when there was a global recession. And how the big surprises awaited him at the
end, to become the most influential technologist in India. Dedication,
Perseverance, Innovation and Team play a big role in startups.
9.
James from the Boston Consulting Group gave the
concluding talk and shared light on a lot of key areas –
·
Myth1 – Bigger Data is Better Data. Actual fact - Size doesn’t matter
·
Myth2 – It’s all about correlation. Actual fact
– Causation remains the key
·
Myth3 – Focus on new ideas. Actual fact – Often
do the same things better
·
Myth4 – Requires big investments. Actual fact –
More capability much cheaper
·
Myth5 – It’s only for advanced firms. Actual
fact – All businesses can benefit.
10.
Check out some of the stalls put up by a few
cool startups - Veda, Nanobi, Germin8, and DataWeave. One thing in common in
all these startups was the factor of Social, Sentiment, and Semantic aspects.
The market looks very promising with all these startups providing a hint
towards it.