John Dowell at Snowball Group writes about the every-growing importance of Big Data and its relevance to venture capital and the investor community.

1. SPOTLIGHT ON
BIG DATA
14th Janurary, 2014
WHITEPAPER BY SNOWBALL GROUP
Level 3, 296 Collins Street
Melbourne Victoria 3000
Phone: (613) 9005 2124
Email: contact@snowballgroup.com.au
www.snowballgroup.com.au

2. “There’s a lot of hype and
popularity surrounding the
new frontier of ‘Big Data’.
There are massive claims
and optimistic predictions
by technology companies,
entrepreneurs and venture
capitalist alike for 2014. Big
Data is a big deal, so what’s
it all really about and what’s
the attraction for investors?”

3. Snowball Group - Spotlight on Big Data
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Spotlight on Big Data
Big Data is a big deal, so what’s it all really about and
what’s the attraction for investors?
Collecting data is not new. We’ve been doing
There’s no doubt the spotlight is on ‘Big
it since the dawn of time. Only now we’re
Data’ and associated analytic tools as they
able to collect and store massive amounts
continue to produce increasing value to the
of information, structured and unstructured,
existence of stored data.
drawn from a wide array of sources. Our
ability to gather information, store it and
then retrieve it has been the preoccupation
of large organisations for the last 100 years.
While we’ve been trying to work that out,
we’ve also been beavering away, in parallel,
to find out how we can create meaningful
relationships between data sets, how to find
the right data to get the desired outcome,
and then apply some logic or algorithm to
make the data useful and valuable in some
way. This hasn’t been without its challenges
in a rapidly changing landscape.
In the last decade a few developments have
transpired to advance our abilities to collect
an enormous amount of data. Once stored
and retrievable we can now apply analytic
tools to use the data in a meaningful way.
It’s producing enormous benefits making the
advent of Big Data and analytics delectably
irresistible.
What is Big Data?
Big Data refers to large sized datasets
where due to their massive size are beyond
the capability of typical database software
tools to capture, store, aggregate, combine,
manage and analyse. That is, in the case of
Big Data the size of structured data is too
large for traditional relational database
management systems (RDBMS) to deal with.

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Snowball Group - Spotlight on Big Data
Big Data is all about taking large amounts
This is done at speed, effortlessly, efficiently
of information and then using tools to
and affordably.
deeply analyse the data to answer complex,
open-ended problems. Through continual
The sheer volume and complexity of data
and successive refinement and abstraction
is typically overwhelming to traditional
we can gain valuable insights resulting in
database systems. To overcome the
positive commercial outcomes.
limitations of traditional data warehousing
systems, software frameworks such as
Hadoop1 and an alternative to RDBMS (SQL
databases) which adhere to ACID2 principles
in Not only SQL (NoSQL3) databases. The
NoSQL approach eliminates schemas and
ACID principles and better supports Big
Data. Of course, the capacity and number
of computers required to partition large
volumes of data into smaller packages and
process them in parallel is vital. The use of
Cloud resources makes this easier.
Making Big Data Possible
In addition to more efficient computer
So what events have accelerated its
power aided by Hadoop and NoSQL, rapid
importance now and in the foreseeable
technological advancement and exponential
future? It begins with a progressive and
growth also occurred in connected devices,
growing need by large organisations
Internet services, social media, image
including government departments and
capture and User Generated Content,
large corporations (especially in financial,
commonly known as ‘UGC’. Together with
insurance and health sectors) to collect and
corporate data, which is mostly unstructured
store data. This is done with the implied
and includes documents, web pages,
understanding that at some stage they will
email, and transactional information about
get to use not just the aggregated data, but
customers, suppliers and their operations,
analyse it at a granular level.
this all represents a massive amount of data.
Together with the information technology
sector and demand driven technological
advancements, large organisations are
progressively gaining access to equipment
capable of storing and retrieving large
volumes of data.
1
Hadoop is an open source software framework for processing massive volumes of data, coordinating local storage and computation across multiple servers acting as a cluster. (i.e.
each server working with a sub-set of the data. Hadoop is a project of Apache Software Foundation. Hadoop is a scalable, inexpensive distributed file system with fault tolerance.
Hadoop’s specialty at this point in time is in batch processing, hence suitable for Data Analytics.
2
ACID stands for adherence to atomicity, consistency, isolation and durability ensuring the data integrity of RDBMS.
3
NoSQL databases or ‘Not only SQL’ eliminate schemas at the expense of adherence to ACID. It tends to create efficiencies enabling analytic tools to perform meaningful and in-
depth analysis.

5. Snowball Group - Spotlight on Big Data
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Data Analytics
Descriptive analytics helps us understand
the relationships between customers and
Up to now organisations looked to capture
products, giving us an indication of what
as much information they could, even
approach we should take in the future. That
with the constraints they faced. They then
aggregated the data for some type of limited
analysis. Alternatively, they would take
samples and try to extrapolate the meaning
is, learn from past behaviours to influence
future outcomes.
“When we talk about
from the data.
‘analytics’ we need to
Since then we’ve learned to harness and
to understand its true
manage the avalanche of an every increasing
value. Capturing lots of
volume of data, constantly being updated
by continuous data feeds. Technology is now
starting to enable us to undertake deep
analytics. By using business intelligence
properly define the term
data, especially digital data has no
value unless you can do something
meaningful with it”.
software, data mining, business analysis
practices, together with new tools and skill
2. Inquisitive analytics
sets we are now beginning to master ‘Big
Inquisitive analytics studies the data to
Data’ at a surprisingly rapid pace.
validate or reject a hypothesis. It includes
There are four basic forms of data analysis
analysis, etc.
that co-exist. All are necessary and occur
consecutively:
an analytic drill down into data, statistical
3. Predictive analytics
Predictive analytics poses the question
1. Descriptive analytics
of what is probably going to happen in
This is the simplest form of analysis helping
the future. It uses a variety of statistical
organisations to understand what happened
modelling, data mining and machine
in the past. Data is taken and condensed
learning techniques and game theory to
into smaller more useful nuggets of
study recent and historical data to predict
information. It basically summarises the data.
the future. You take what you have and what
It’s estimated that 85% of data, especially
you don’t have and predict in a probabilistic
from social media is treated with descriptive
way. Predictive analysis is very useful in
analytics. For example, it looks at the data
determining risks and opportunities in the
to describe the current situation in a way
future.
that makes trends, patterns and exceptions
become apparent.

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Snowball Group - Spotlight on Big Data
Historical and transactional data is used
to identify patterns. Statistical models and
algorithms are then applied to capture
relationships in various data sets. With
predictive analytics you have to use as much
data as possible to get better predictions.
4. Prescriptive analytics
This is the final stage of the Big Data
analysis process. This is used to prescribe
an action so business decision makers can
So where to with Big Data now?
take the information and act on it. That is,
“The use of Big Data is made
you take the predictions and act on it in a
up of large pools of data
certain way, tracking the feedback from the
capable of being brought
action taken. It answers the question formed
together and analysed to
from descriptive to predictive analysis,
discern patterns and enable
namely, “So what?” and “Now what?”
better decision-making. Big
Data will become the basis of competition
Prescriptive analytics uses mathematical
and growth for firms, enhancing
science, business rule algorithms, machine
productivity and creating significant value
learning and computational modelling
for the World Economy by reducing waste
techniques. It tries to see the effect of future
and increasing the quality and experience
decisions so you can adjust them before
of using products and services”.
you make the decision. This is an important
area of Big Data. Analytics has a long way
The Big Data boom is already here. It’s
to go, but is no doubt the new frontier. Once
being used for more effective marketing,
mastered, Big Data analytics will pay big
customer profiling, product development,
dividends. Ayata is the company who have
risk management, and achieving greater
pioneered prescriptive analytics with their
operational efficiencies. Companies are
patented technology.
mining and processing petabytes of
4
information to gain an insight into customer
behaviour, supply chain efficiencies and
improvement to business performance.
Those who’ve been early adopters have
gained a significant lead over the rest of
corporate world.
4
Ayata was founded in 2003 to pioneer the complex R&D required to combine different disciplines of mathematical sciences, machine learning and computational disciplines for developing
Prescriptive Analytic software. Ayata incorporated in 2009 to commercialise its technology. Its customers today are Dell, Cisco, Microsoft and Apache Corporation. www.ayata.com

7. Snowball Group - Spotlight on Big Data
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According to a survey of 400 companies by
Bain & Company5 in 2013, organisations
leading in the use and investment in Big
Data have outperformed their competitors
financially; being five times more likely to
make quicker at making business decisions
than market peers, and three times as likely
to execute decisions as intended.
In fact the use of Big Data is becoming
crucial for leading companies to outperform
their competitors. It’s becoming evident in
Where we think Investment in
Big Data should be?
most industries, established companies and
new entrants alike will look to leverage
Big Data is creating new growth
data-driven strategies to innovate, compete
opportunities including those aggregating
and capture value. Early examples include
and analysing industry and individual
healthcare and pharmaceuticals, discovering
company data. These companies sit in the
benefits and risks not evident in clinical
middle of large information flows where
trials.
data about customers, suppliers, products,
consumer preferences and customer intent
For those looking to invest in the next best
are captured and analysed. These are the
thing, there’s no doubt the evolution of Big
companies employing specialists who can
Data has arrived. Those who use Big Data
apply the analytic tools and interpret the
effectively will gain a competitive edge
data to give it real value.
making its adoption irresistible. This isn’t an
overnight phenomenon. This has been in the
However from a venture capitalists point of
making for several decades.
view our focus is not on equipment, software
or the companies specialising in analytics.
To be a participant of the Big Data game
Instead we’re interested in companies that
you need to have access to a large volume
can capture and store large quantities of
of data (format that allows for easy
data capable of deep analytics resulting
access and analysis), you need to be using
in a real competitive advantage, increased
advanced analytic tools such as Hadoop
earnings and improvement in company
and NoSQL, and you need the people with
valuation.
the skills to use them. In fact you need
people with exceptional skills in the area of
mathematical and computer science.
5
Why do we like Big Data? Not because it’s
the new fad and we just want to get on the
A Bain & Company study in 2013 of 400 large companies in the USA showed companies with the most advanced analytics capabilities are outperforming competitors by a wide margin.

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Snowball Group - Spotlight on Big Data
bandwagon. No, it’s because we truly like its
in. It’s a bit of the herd mentality, and a
core proposition and the value it can bring
bit of risk management. A couple of years
to a mediocre company and make it a star.
ago, online companies that didn’t generate
revenue and had no identifiable earnings
The insights it provides and support to
model, but could generate a lot of traffic
better decision-making give companies
would be considered high risk and too be
a competitive edge, making them an
avoided; remnants from the dot com boom
interesting proposotion to invest in.
and bust era. How things have changed.
The lesson most venture capitalists learn
is never back a horse sitting too far out in
front half way through the race. This writer
for one knows first hand it doesn’t matter
how much of a visionary you are, you can’t
get investors to come with you if you choose
an opportunity that’s a little speculative, a
little ahead of its time and makes investors
uncomfortable. You can’t expect investors
to stick their heads out too far, usually for a
long period of time.
The fact is, Big Data is already here and
being used by large financial, insurance,
health and industrial corporations. As a
consequence it can be considered a real and
genuine proposition. Large companies are
investing serious funds and considerable
in-house resources to Big Data.
Nevertheless, rather than focusing on
the Big Data analytic component and
mathematical scientists, the safe investment
still remains with entities, especially early
stage companies that show great potential
to attract high volume transactions and are
capable of capturing large amounts of data.
This is the type of commercial opportunity
investors are more comfortable to invest
Think of the breathtaking valuations we’ve
seen even before one cent of revenue was
generated. They all have something the
masses are attracted to like moths to a
flame. The concept of working out how to
monetise comes later. Think of Facebook,
LinkedIn and Twitter, followed by Instagram,
Tumblr, Waze, Dropbox and their massive
valuations. These successes have driven
valuations of the next wave including
Pinterest, Snapchat etc. right out there in
another universe.
The point being made is that investors don’t
have to be attracted by revenue and profit
because they know ventures attracting, or
investor believe will attract, large amounts
of data are worth investing in, irrespective of
unrealistic valuations.

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A Venture Capitalist’s
Point of View
you can combine the present with the
future and still go some way to satisfy the
investment criteria. Introducing analytics
In the case of online ventures, Snowball
may even be a subsequent investment event,
Group prefer to focus on transactional
or a bolt on acquisition. Irrespective, there’s
online platforms such as global eCommerce
no doubt bringing the two together will
portals, high volume interaction sites,
lead to improvement in earnings and strong
and ‘Freemium’ type business models
capital growth. Given rapid developments in
targeted at large identifiable industry
technology and skills, as well as the ongoing
sectors involved in business-to-business
focus it’s getting, tevhnological advancement
transactions. In particular we like online
and the commercial benefits that will flow
videos, especially when it brings with it rich
from that is more likely to be sooner than
content and viewer information, perfect for
later. This is music to the ears of VCs.
deep analytics, profiling and a plethora of
applications. This is an enormous growth
area about to get bigger with swags of
new devices soon to be released such as
wearable glasses technology.
However for Snowball Group it doesn’t just
stop there. We apply a rigorous screening
process when reviewing early stage ventures.
A major requirement for us is to like the core
proposition. Just collecting unstructured data
from a busy website may be trending with
investors at the moment but it won’t last
Why is Big Data still a
Cautionary Tale?
if you don’t do something with the data to
monetise it.
Big Data has the potential to drive efficiency
and quality in an organisation’s operations
For venture capitalists you need to balance
and earnings. It also has the potential to
your investment decision by getting in early
better profile customers enabling better
but not too far ahead of the current trends.
tailoring of products. Big Data can be used
It has to be what is palatable to investors
to develop the next generation of products
in the present. Investing in online ventures
and services. It can even substantially
attracting large volumes of usable data
improve decision-making, minimise risk, and
satisfies this. Introducing Big Data analytics
unearth valuable insights otherwise hidden.
is the future. By attaching it to the former

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It sounds like the panacea for all the ills
new talent as the demand for Big Data and
mankind faces. It may be too good to believe
the analytics is rapidly growing. Even once
and probably is. The tsunami of information
universities mobilise to adjust their course
flow is overwhelming and even if it’s
curriculum and master degrees, the dynamic
quantifiable a lot is not strategically useful.
nature of the Big Data industry will change.
It should be treated with some degree of
scepticism. Just capturing more data doesn’t
As a result of companies increasingly
necessarily make companies any smarter.
looking to Big Data to help them make
The data is one side of the equation, how
informed decisions they also need to push
correct the analysis applied to the data
for advanced data science skills. This has to
is the other. One has to also remember
be done in conjunction with having a Big
we live in a dynamic world where things
Data strategy so you know what the Big Data
change constantly. Making critical business
scientist’s skill should be.
decisions based on data alone, especially
when its machine-learned results based on
past or even present information, may lead
to catastrophic outcomes. It must also be
remembered that not all strategically useful
data is quantifiable.
Big Data skills are a blend of information
management, technology management, as
well as analytic statistical and mathematical
skills. They also have to be equipped with
business and content knowledge to data
mine or extract the right data. Big Data
The most worrying aspect of Big Data is its
personnel will need to know how to utilise
dependency on unique and advanced skills
high performance computing environments
in mathematical sciences, data sciences and
as well as mathematical and computational
statistical analysis.
software filtering through thousands of
datasets to find the valuable relationships.
The success of Big Data will only happen
if organisations hire enough people who
actually understand Big Data to collect,
preserve, and then retrieve the data. They
need to be able to analyse a lot of data
in an accurate, meaningful and relevant
way. The problem is right now there aren’t
enough data scientists with the required
skills to meet demand.
The shortage in skill is quite large and
universities are not generating enough

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Conclusion
Although a lot of hype surrounds Big Data
a reality now and appealing to investors.
and the analytic tools used to predict and
Companies who at the same time look to
prescribe commercial decisions in advance
the future combining this with the deep
to ensure success, it comes with some
analytic capabilities provide upside to the
reservation. It may not be the panacea for
investment opportunity’s valuation over a
everything, but to a Venture Capitalist it
relatively short time horizon.
contains the sort of elements making it an
attractive opportunity.
For a private equity investor willing to
take risk for greater gains, investment
Companies capable of collecting and
opportunities involving Big Data is worth
managing a massive amount of data,
considering.
whether received from customers, suppliers,
internally within an organisation’s operation,
or from large scale online transaction
platforms and interactive social media, are
This document is provided by Snowball
advisors. Before making any decision or
Group Pty Ltd for general guidance only,
taking any action, you should consult with a
and does not constitute the provision of
professional advisor who has been provided
legal advice, accounting services, investment
with all pertinent facts relevant to your
advice, written tax advice under Circular
particular situation. The information is
230 or professional advice of any kind. The
provided ‘as is’ with no assurance or guarantee
information provided herein should not be
of completeness, accuracy, or timeliness of the
used as a substitute for consultation with
information, and without warranty of any kind,
qualified technology specialists, professional
express or implied, including but not limited
financial and investment adviors, professional
to warranties or performance, merchantability
tax, accounting, legal, or other competent
and fitness for a particular purpose.

12. PRIVATE EQUITY INVESTMENT FIRM
GLOBAL CORPORATE ADVISORY SERVICE
Author:
John Dowell
Executive Director and Co-founder at Snowball Group
John Dowell has over 30 years of experience in corporate finance, venture capital and the ICT
sector. He’s a leader in areas of e-commerce, IT infrastructure, and business intelligence. He has
had extensive experience leading top global technology companies.
Level 3, 296 Collins Street
Melbourne Victoria 3000
Phone: (613) 9005 2124
Email: contact@snowballgroup.com.au
www.snowballgroup.com.au