How ‘Big Data’ Can Create Significant Impact on Enterprises? Part I: Findings and Implications from Longitudinal Analysis and Systematic Review

Pradeep Singh. Int. Journal of Engineering Research and Application www.ijera.com
ISSN : 2248-9622, Vol. 6, Issue 12, ( Part -4) December 2016, pp.01-07
www.ijera.com 1 | P a g e
How ‘Big Data’ Can Create Significant Impact on Enterprises?
Part I: Findings and Implications from Longitudinal Analysis and
Systematic Review
Pradeep Singh*, Naveen Pandey**
*Research Analyst, Current Analysis Group, Global Data Research Center, India
** Assistant Professor, Department of Decision Sciences, University of Petroleum & Energy Studies, India
ABSTRACT
Big data is the latest buzz word in the BI domain, and is increasingly gaining traction amongst enterprises. The
prospect of gaining highly targeted business and market insight from unmanageable and unstructured data sets is
creating huge adoption potential for such solutions. The scope of big data moves beyond conventional enterprise
databases to more open environments, covering new sources of information typically relating to various social
networking sites, wikis and blogs. Moreover, advancements in communications and M2M technologies are also
contributing to the massive availability of big data.
Keywords: Analytics, BI, Big Data, Business Value, Enterprises, IT Services, Hadoop, NoSQL, Visualization,
SMEs
I. INTRODUCTION
For the last few years, the analytics domain
has been greatly impacted by the hype around „big
data‟, and organizations are looking to understand
this concept and use such solutions to analyze huge
volumes of structured and unstructured data [1].
With the help of platforms such as Hadoop
and NoSQL, enterprises are looking to mine and
analyze the raw data available from social
networking sites to get useful insights about
customer behavior, buying patterns, and changing
market trends [2]. Moreover, with the addition of
certain interactive and visualization features, big
data tools can also be used by line of business users
other than senior executives and analysts, which is
expected to increase the penetration rate of such
solutions amongst enterprises.
Meanwhile, BI vendors are also looking to
tap this growing market and are investing widely to
develop and improve their capabilities in the big data
space. Furthermore, the study expects that in the
coming years, vendors will look to provide big data
solutions in a virtualized environment. In addition,
BI vendors are working on integrating Hadoop
solutions with advanced BI tools and data discovery
& visualization tools in order to help customers to
analyze data in a visually compelling and interactive
interface. The study therefore notes that the market
for big data has tremendous potential to transform
the BI segment, and IT vendors will have to enhance
their offerings in this space to make sure that they do
not lag behind their counterparts [3]. The below
mentioned Table (1) and Fig (1) illustrates the
number of small enterprises responded for ICT
survey.
Table 1: Small enterprises ICT survey data
geographic breakdown
Countries Count
Spain 75
Italy 74
France 74
UK 68
Russia 66
China 62
Brazil 61
Germany 60
US 54
India 40
Australia 37
Canada 36
Others 496
6%
6%
6%
6%
6%
5%
5%
5%
5%3%3%
3%
41%
Spain
Italy
France
UK
Russia
China
Brazil
Germany
US
India
Australia
Canada
Others
1203 respondents
Fig.1. Small enterprises' ICT survey data geographic
breakdown
RESEARCH ARTICLE OPEN ACCESS

ENTERPRISES TAKEOUTS
Enterprises: need to adopt various
analytical and visualizations tools and skills to
generate useful insights from the big data they have
generated. IT departments: need to devise a robust
data governance plan to reduce security breaches.
Employees: need to be trained properly to make use
of these advanced analytical tools, failing which the
investment will go in vain.
The below mentioned Fig (2) shows the
overall ICT budget change pattern (flat, growth or
shrink) from FY 2013-14 to FY 2014-15.
Decrease 6%or
more
Decrease slightly
(1%-5%)
Flat (0%)
Increase slightly
(1%-5%)
Increase
significantly (6%+)
2013-14 (%) 9% 20% 41% 25% 5%
2014-15 (%) 7% 14% 29% 37% 14%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
%ofrespondents
1203 respondents
Fig.2. ICT budget change (growth or shrink) from
2013-14 to 2014-15
II. SUPPORTING ARGUMENTS AND
EMPIRICAL EVIDENCES
1.1 THE FOUR LAYERS OF A BIG DATA
SYSTEM
In order to draw actionable insights from
raw statistics or snippet of unstructured data, data
has to pass through different layers [4]. The first
layer has to do with data sources. These sources
could include sales records, customer database,
feedback, etc. The second layer is the data storage.
As the amount of data generated and stored increases
exponentially, accessible systems and tools such as
Apache Hadoop DFS can be used to deal with the
task. These tools will help in categorizing the data.
Third, when firms want to use the data they have
stored to find out something useful, they will need to
process and analyze it. A common method is by
using a MapReduce tool. Essentially, this is done to
choose the aspects of the data that they want to
analyze, and then put it into a format from which
insights can be derived. The fourth layer is the data
output. This is the stage where the insights gleaned
through the analysis are passed on to the people who
can take necessary action that benefits the business.
The analysis must be clear and concise. The output
can be in the form of reports, charts, figures and key
recommendations [5].
1.2 DATA HELPS ENTERPRISES GAIN
COMPETITIVE EDGE
Organizations can significantly accelerate
the growth of their business by doing enormous
things with data [6]. Data can enable companies to
gain competitive edge in six ways. First, the modern
business landscape is such that organizations
compete for information. As a result, organizations
ought to have better and well performing
information to get ahead in competition. Better
information can enable firms to take smart decisions.
Second, businesses can turn the data into active
information that enables them to achieve real goals.
Third, companies can use the data to move forward
in directions that can enhance sales and reduce costs.
Fourth, the data that has been accumulated over the
years must be integrated with rest of the business.
This in turn helps in connecting the dots between
previous, current, and potential future transactions.
Fifth, it is important to ensure that everyone in the
company has access to technology and data. Jobs
can be done better when employees are equipped
with data. Sixth, businesses should ensure that they
always have high quality data. In short, data is a big
asset for companies [7].
1.3 FIRMS RUSH TO DEVELOP SMART
DATA VISUALIZATION TOOLS
Advances in information technology, social
networking, and communication have contributed to
the massive availability of big data, paving way for
development of interactive data visualization tools.
The traditional visualization tools provide visual
representation of data in a static and non-interactive
nature that requires more time to understand and
analyze. On the other hand, interactive data
visualization, which was developed as an ad hoc
solution to address specific questions within specific
set of data, has become hugely popular. As this tool
allows better understanding of the relationships and
trends in data sets and enables quickly drilling down
data to the smallest unit, organizations of all sizes
are rushing to develop better and faster data
visualization tools. This in turn is causing an
irrational expectation that data visualization is the
answer for handling big data. However, it is
necessary that data analysts and programmers ensure
they are asking the right questions and utilizing the
right methods in order to analyze the data. Further,
they could also include human visual perception
capabilities into design. The data visualization tools
should ideally be providing information on what is
expected and decode what is not expected [8].

1.4 UNLOCKING BIG DATA CAN OPEN
UP OPPORTUNITIES FOR SMES
Big data offers several opportunities for
SMEs (small and medium enterprises); however, due
to the cost factor and complexities of analyzing the
data, these firms are not able to effectively unlock
the potential of big data. In order to derive benefits
from big data, SMEs need to follow certain steps.
The first requirement is to thoroughly assess what
big data can offer. They can begin the big data
journey on an experimental basis. In case of a crunch
in resources, they can outsource their data. Second,
firms can leverage big data to test their assumptions
against the available information and create
scenarios. This will facilitate decision-making
processes, both tactical and operational. Third, given
that big data will lead to changes in the set format of
decision-making process, organizations must be
prepared to innovate. In fact, big data should be seen
as a long-term learning experience rather than just as
a short-term investment. As companies cannot
achieve additional value without changing their
culture, it is imperative that they develop a culture
where in data-driven decision-making is the norm,
not the exception. Fourth, firms need to be clear on
their privacy policies to gain trust from stakeholders
and convince them that the data is being used for
their benefit [9].
The below mentioned Table (2) and Fig (3)
illustrates the number of small enterprises responded
for ICT survey across the industry verticals. The
respondent size for education counts for 134,
similarly respondent size for healthcare counts for
86.
Table 2: Small enterprises‟ ICT survey data industry
breakdown
Industry Count
Education 134
Manufacturing 130
Retail 130
Telco/service provider 94
Financial markets 94
Media 94
Healthcare 86
Utilities 74
Energy 72
Government 72
Retail banking 71
Insurance 70
Pharmaceuticals 69
11%
11%
11%
8%
8%8%
7%
6%
6%
6%
6%
6%
6%
Education
Manufacturing
Retail
Telco/serviceprovider
Financial markets
Media
Healthcare
Utilities
Energy
Government
Retail banking
Insurance
Pharmaceuticals
Fig.3. Small enterprises' ICT survey data industry
breakdown
III. KEY ACTIONS BEFORE THE
ADOPTION OF BIG DATA
1.0 FIVE WAYS TO USE BIG DATA
With big data becoming influential,
companies are quickly embracing this solution. In
order to successfully use big data, companies should
follow certain key steps.
1. Collecting data without a proper goal will result
in huge amount of data with little purpose or
direction. Therefore, it is important to have a
clear goal in mind before collection of the data.
This will help companies in knowing what kind
of data they should be going after, and enables
them to form a proper data strategy.
2. Firms should base their business decisions on
the data collected, rather than relying on
intuition or instinct.
3. Collecting data is just one step of the process;
interpreting and analyzing to get meaningful
insights from the collected data requires
different sort of skills and expertise. Hence, it is
important that businesses have the right people
to do the job. They can either hire data experts
or train people who are already employed in the
company.
4. It is difficult for a human mind to grasp the
massive amount of data being generated. As a
result, enterprises should have the latest
technology or solution to process the data that is
being generated at incredible pace.
5. In order to gather the data, companies need to
go where customers are; in today‟s world,
customers are using social media and firms
should therefore be tapping social media [10].
2.0 BIG DATA COMES WITH BIG ISSUES
Big data offers several benefits, such as
competitive advantages and operational efficiency.
However, big data also comes with big issues, writes
Simon Campbell for Biz Community.com. Not
having a good data governance plan can lead to
security breaches, unreliable data, and unexpected
expenses. Given the complex nature of big data, it
cannot simply be processed using traditional data

processing methods. Businesses no longer deal with
megabytes or gigabytes of data; in fact, they deal
with terabytes and petabytes of data, which come in
several forms and through different sources. In
today's competitive landscape, it is imperative for
businesses to derive actionable insights from data as
business decisions are hinged on that. However, the
regular database and warehouse management tools
are unfortunately inadequate. In order to derive
complete value of big data, collection and analysis
of the data is not enough; businesses need to know
how and when to use this data. Data can also turn
out to be a liability, especially in the event of loss or
theft of data. This data could be proprietary
company information, financial credentials, login
details, or intellectual property. Therefore, firms
need to ensure that good security, data management
tools, and solid governance, compliance standards
and structures are in place [11].
IV. RELATED WORKS
Three areas where big data can be helpful
for start-ups: Due to limited budgets, small and start-
up firms face the hurdle of eliminating waste and
finding ways to experiment and expand. However,
companies will be able to make use of their limited
resources with big data. With this added efficiency,
businesses can increase their capital and revenues
easily. There are three important areas where big
data can particularly be implemented [12].
First, tracking customers and potential
customers is very difficult for small businesses.
They might invest more or less than required, both
of which are not ideal for a fledgling business. This
is where big data come into use - it helps in gauging
how much should be invested in marketing and
where that money should be spent.
Second, pricing plays a crucial role; if
companies get their pricing wrong, they can quickly
be out of business. Businesses need to be careful in
pricing their products. The right price makes all the
difference - it brings in enough capital, and at the
same time will bring customers in again and again -
this is one area where big data can be extremely
helpful.
Third, big data helps organizations improve
performance of their either already superior
employees or improve the efficiency of a struggling
workforce. Big data has proven that it is effective in
motivating and improving employees‟ performance
in various sectors. As a result, it enables companies
to save time and money in hiring and training new
employees.
V. RECOMMENDATIONS FOR
ENTERPRISES TO HARNESS BIG DATA
“Ecommerce companies are extensively
using big data to better understand their customers
and provide services and experiences tailored to
each individual and achieve competitive advantage.”
For many firms, it is no more a question of
whether to use big data solutions or not; rather it is a
matter of what kind of tools to be deployed and how
much to be spent. Companies can harness big data in
a few ways [13]:
 Ecommerce companies can choose in-house
route and hire data scientists to handle their data
needs. Collecting data, analyzing and presenting
and spotting trends will help organizations in
taking quick actions.
 Outsourcing big data needs can be another
option. A retailer can seek the help of firms and
let them crunch the numbers and generate
insights, so that the retailer can focus on selling
products, take care of customers, and grow the
business.
 Cash-strapped companies can take the „do-it-
yourself‟ approach by making use of
inexpensive tools such as Google Analytics.
reveals small enterprises‟ overall ICT budget
allocation in the FY 2014 and FY 2015 (how did
enterprises spend their overall ICT budget in FY
2014? How will this change in 2015?) . The survey
result shows that small enterprises allocated 28%
and 22% of their overall ICT budget to hardware and
software respectively in FY 2014 and it remains the
same for the FY 2015.
Table 3: Small enterprises‟ (external) ICT budget
allocation, 2014 and 2015
Category 2014 2015
Hardware 28% 28%
Software 22% 22%
Services 16% 16%
Communications 15% 15%
Consulting 12% 12%
Other 8% 7%

28% 28%
22% 22%
16% 16%
15% 15%
12% 12%
8% 7%
0%
20%
40%
60%
80%
100%
2014 2015
ExternalICTbudget(%)
Hardware Software Services Communications Consulting Other
1203 respondents
Fig.4. Small enterprises‟ ICT budget change from
2014 to 2015
VI. ISSUES AND CHALLENGES
1.0 STRIKING A BALANCE BETWEEN
BENEFITS OF BIG DATA AND PRIVACY ISSUE
ESSENTIAL
“A vast amount of data is being floated
around the world due to the ubiquitous data-driven
technology.”
Every interaction within the digital realm,
be it on smartphone, computer, through credit card
transactions, is collected, stored, accessed and
analyzed in real-time, with accuracy. Though big
data provides many benefits, customers feel they are
being constantly monitored. Therefore, it is
important to strike a balance between the benefits of
big data and the privacy concerns of customers [14].
There is the underlying issue of privacy when it
comes to big data:
1. People are uneasy about giving personal
information as it could lead to unmonitored
distribution of the information to advertisers,
government and other organizations.
2. Big data enables enterprises to deliver insights
accurately with maximum impact, which also
helps decision-makers to act thoughtfully. For
this however, they need to be adequately
equipped in analyzing and visualizing the
information, whilst avoiding the ethical pitfalls.
3. The ability to measure and study big data can
help firms in dissecting customer patterns
effectively and identifying emerging trends
swiftly and accurately.
illustrates various factors influencing small
enterprises‟ decision to choose an IT provider in FY
2014. Various factors such as geographical reach,
contract flexibility, financing options payment
terms, expertise in industry and many others have
been rated by respondents on a scale of one to four
and shown below.
Table 4: Factors influencing small enterprises'
decision to choose an IT provider
Factors Average rating
(On a scale of
one to four)
Geographical reach 2.7
Financing
options/payment terms
2.7
Contract flexibility 2.8
Breadth of solution
offerings
2.8
Specific functionality
expertise/depth
2.9
Expertise in industry 2.9
Financial stability 3.0
Leading-edge technology 3.0
Price 3.0
2.5
2.6
2.7
2.8
2.9
3.0
3.1
Geographical
reach
Financing
options/payme…
Contract
flexibility
Breadth of
solution offerings
Specific
functionality…
Expertise in
industry
Financial stability
Leading-edge
technology
Price
Fig.5. Factors influencing Small enterprises'
decision to chose an IT provider
2.0 BIG DATA CHALLENGES EVENTUALLY
IMPEDE PERFORMANCE
“Big data challenges often impede big
organizations from taking complex decisions, which
in turn impacts performance.”
In order to deal with this challenging
decision environment, some organizations are
seeking analytical firepower that blends the right
analytical software, so that it is finely tuned to
perform on server hardware [15].
Companies can leverage big data with the
right technology. By using appliances, companies
can equip themselves with the ability to explore data
and find insights in a timely manner. The
opportunity of using analytical appliances
effectively comes in three aspects:
 First, in order to enrich the decision making
process, companies should have the ability to
tap a broad array of data from internal and
external sources.
 Second, enterprises and businesses need to have
the ability to quickly analyze collected data and
gain insights from it.

 Third, interpretation should be in tune with the
business role and this information must be easy
to use.
3.0 SMALL DATA IS THE PRODUCT OF
BIG DATA ANALYSIS
“Small data is the product of big data
analysis even though it may seem to be contradicting
the whole big data movement.”
The conventional data analysis dealt with
databases filled with product information, customer
information and other data [16]. However, it was
difficult to efficiently analyze the high volume of
data as companies did not have the capability to
address the corresponding requirement for increase
in scale and data processing ability. These
shortcomings were addressed by creating smaller
data sets. However, even these smaller data sets had
shortcomings as often there was a mismatch between
the data and working context [17].
1. Initially, enterprises had to face problems in
analyzing big data, due to infrastructure
problems. However, specific technologies have
addressed these shortcomings; in turn helping
firms to manage and manipulate big data [18].
2. If enterprises still consider big data as a
challenging task, they might want to wait a year
or two: the emergence of ubiquitous machine
data is just around the corner.
3. Enterprises should not be scared; rather, they
should be well prepared. Enterprises will have
more data than they can imagine, and the means
to capture and manage data of this scale already
exists [19, 20].
VII. CONCLUSIONS AND FUTURE
RESEARCH
“Big Data has big potential!”
In summary, the proposed paper analyzes
the development related to Big Data technologies
and adoption of these technologies in large, small
and medium-sized enterprises. The paper represents
a holistic view about the benefits and challenges
associated in direct and cross-platform application of
these technologies across all sizes of enterprises.
However, in future, more attention would be made
towards developing cross-platform interoperability
of Big Data technologies in such a manner that a
new version could use the functionalities of its
previous version. This development is also expected
to facilitate enterprises to gain maximum leverage of
Big Data technologies in their business operations
along with making better and faster decision-making
based on the insights gathered from data collected.
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Business Ethics. Ethical Decision Making and
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2011)
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Agriculture Organization Of The United
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analytics-106272.pdf
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ABOUT THE AUTHORS
Pradeep Narayan Singh is an illustrator and author,
started his career writing
for white papers,
conference papers, and
research reports. At
present he is working as
“Research Analyst” at
Current Analysis Group,
Global Data Research
Center, Hyderabad, India.
He has written about latest
technological advancement in data center, to
upcoming technologies in Telecom and IT. He has
experience in Research and Analysis (Qualitative
and Quantitative) for Telecom and IT industry. This
is where; he proposes strong acumen towards the
technology and related aspects and continuously
looks forward to the changing technology and
business aspects. He has completed B.Tech in
Computer Science & Engineering from G.B.
Technical University, India and MBA in
Management Information Systems from University
of Petroleum & Energy Studies, India.
Naveen Chandra Pandey is an “Assistant
Professor” at the Department of Decision Sciences,
University of Petroleum
& Energy Studies, India.
He has extensive
experience in industry as
well as in academics; his
research areas include
Project Management, IT
Applications and
Management Information
Systems. He has
completed B.Tech in Mechanical Engineering, from
Kamala Nehru Institute of Technology, Sultanpur,
India and MBA in Information Systems
Management, from University of Petroleum &
Energy Studies, India. At present he is pursuing
Ph.D, from University of Petroleum & Energy
Studies, India.

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