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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
“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?”
Snowball Group - Spotlight on Big Data

3

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.
4

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.
Snowball Group - Spotlight on Big Data

5

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.
6

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
Snowball Group - Spotlight on Big Data

7

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.
8

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.
Snowball Group - Spotlight on Big Data

9

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
10

Snowball Group - Spotlight on Big Data

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
Snowball Group - Spotlight on Big Data

11

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.
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

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Snowball Group Whitepaper - Spotlight on Big Data

  • 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 3 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.
  • 4. 4 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 5 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.
  • 6. 6 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 7 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.
  • 8. 8 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.
  • 9. Snowball Group - Spotlight on Big Data 9 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
  • 10. 10 Snowball Group - Spotlight on Big Data 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
  • 11. Snowball Group - Spotlight on Big Data 11 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