Big Data Analytics and its Impact

This assignment delves into the profound influence of big data analytics on various organizational aspects. It examines the core concepts of big data, its analytical techniques, and the multifaceted impacts it exerts on business operations, decision-making, and overall performance. The assignment encourages a critical analysis of case studies and real-world examples to illustrate the practical applications and potential challenges associated with big data implementation.

Running head: BIG DATA 1
The impacts of Big Data on organizations
Name:
Institution Affiliation:

BIG DATA 2
Executive Summary
The big data has the potential to revolutionize the business operation. Despite the high
operational as well as strategic impacts, there have been a paucity of the empirical research to
access the potential of the big data. The big data is the new technology which has been
implemented by many organization in order to improve the existence of the business as well as
create the new business opportunities. The purpose of this research is to obtain information in
regards to the impact of the big data to organizations and provide an empirical evidence in
regards to its impacts.
There were three different organization which were selected for the study purpose, and data was
collected using the data collection methods. This study evidently found that the Big Data is
impacting every industry and every organization. Currently, this technology has offered many
business different benefits through; making of the data available, bringing the integration to the
processes of the business, and insights from the data (Waller & Fawcett, 2013). The experiences
of these businesses also proved that the introduction of the technology could pose challenges to
the business. In this paper it would present an interpretive framework which analyzes the
definitional perspectives as well as the applications of the big data. Moreover, the research will
provide a broaden understanding of the big data as well as its role especially in capturing on the
value of the organizations. The synthesis of the diverse aspects that are within the literature on
the big data offers a deeper insights into the achieving a value through big data strategy along
with the implementation.

BIG DATA 3
Table of Contents
CHAPTER ONE........................................................................................................................................5
INTRODUCTION TO THE STUDY.......................................................................................................5
1.0 Introduction.........................................................................................................................................5
1.1 Background to the study...............................................................................................................5
1.2 statement of the problem...............................................................................................................5
1.3 Purpose of the study......................................................................................................................6
1.3.1 Objectives of the Study..............................................................................................................6
1.4 Research questions........................................................................................................................6
1.5 Significance of the study................................................................................................................6
1.6 limitation of the study....................................................................................................................7
1.7 Scope of the study..........................................................................................................................7
CHAPTER TWO.......................................................................................................................................8
LITERATURE REVIEW.........................................................................................................................8
Introduction 1.0.........................................................................................................................................8
2.1 Information technology.......................................................................................................................8
2.2 Big data................................................................................................................................................8
2.2.1 Definitions and features of the big data...................................................................................9
2.2.2 Big data and its significance.....................................................................................................9
2.2.3 Challenges of Big Data...........................................................................................................10
CHAPTER THREE.................................................................................................................................12
RESEARCH DESIGN AND METHODOLOGY..................................................................................12
3.0 Introduction.......................................................................................................................................12
3.1 Research Design.................................................................................................................................12
3.3 Sample and Sampling technique.......................................................................................................12
3.4 Data Collection Instruments.............................................................................................................13
3.5 Validity and Reliability.....................................................................................................................13
3.6 Data collection procedure..................................................................................................................13
3.7 Data analysis and presentation..........................................................................................................13
CHAPTER FOUR...................................................................................................................................15
DATA ANALYSIS AND PRESENTATION.........................................................................................15
4.0 Introduction.......................................................................................................................................15
4.1 Response Data....................................................................................................................................15

BIG DATA 4
CHAPTER FIVE.....................................................................................................................................18
SUMMARY, CONCLUSION AND RECOMMENDATION...............................................................18
5.0 introduction........................................................................................................................................18
5.1 Summary of the findings...................................................................................................................18
5.1.1 Potential impact of the big data analytic on the organization.............................................18
5.1.2 How the data and data analytic enhance the performance of the organization.................18
5.2 conclusion...........................................................................................................................................19
5.3 Recommendations..............................................................................................................................19
5.4 suggestions for the further research.................................................................................................19
5.5 limitations...........................................................................................................................................19
6. References.............................................................................................................................................20

BIG DATA 5
CHAPTER ONE
INTRODUCTION TO THE STUDY
1.0 Introduction
This project aims to investigate the impacts of the Big Data to the organizations. The new
information technologies such as the Big Data is one of the technologies that could be disruptive,
hence change on how the organization undertake and performs their activities (Agrawal, Das &
El Abbadi, 2011). Currently, most of the researches which have been undertaken on the topic of
the Big Data have been theoretical; there has been hardly any empirical study on the topic. In this
introduction chapter it will fulfil various goals which are examined as follows in regards to this
research study.
1.1 Background to the study
Why should the academics as well as the practitioners be interested in undertaking about the
impacts of the big data? The simple answer to this question would be Big Data concept has the
potential of transforming the entire organization process and this paper would play main role to
conceptualize on this approach (Braganza, Brooks, Nepelski, Ali & Moro, 2017). In this research
study, it will examine the impact of the big data on the organizations. The extant literature will
highlights the big data as the next big things in the innovation.
1.2 statement of the problem
The information technology has brought forth to the importance of the improvements in the
operations of the business (George, Haas & Pentland, 2014). The big data is believed to offer
both a challenge as well as opportunity for the businesses. There has gaps in the research of the
impact of the big data in organization and the existing research is all theoretical, this research

BIG DATA 6
will address this and provide an empirical study. It will highlight how the big data has impacted
on the businesses.
1.3 Purpose of the study.
The main objective of this study is to investigate the impacts of the big data on the organizations.
1.3.1 Objectives of the Study
 To investigate the impact of the big data to the organization process?
 To find out how big data analytics could impact the performance of an organization?
1.4 Research questions
It is important to possess a definite objective as to the reasons this study would be carried out
based on the study issue description provided above, it really is clear the aim of the study would
be to offer empirical attestation regarding the influences of big data to the businesses (Hussain &
Roy, 2016).
 What are the potential impact of the big data analytic on the organization?
 How does the fit between data, data analytic tools, and the task influence the performance
antecedents of an organization?
1.5 Significance of the study
This research is aimed to be of the scientific in addition to practical significance. Even though
the data has become the modern form for the capital in addition to the source for the competitive
advantage, the principle off the big data is a whole new emerging concept for many individuals
to gain. This research will fill the gap, by providing the empirical study which not many research
has been done

BIG DATA 7
1.6 limitation of the study
The researcher may encounter constraints from the respondents where some of them could hold
the information due to the confidentiality aspects in the workplace, but as a researcher I will be
able to convenience them that the information will be confidential and it will be utilized only for
the purpose of academic.
1.7 Scope of the study
The scope of the study will be within the setup of the banking institution with a target population
of approximately seventy eight employees and a sample size of thirty nine in the organization.
The research is aimed at addressing the impacts of the big data on organizations.

BIG DATA 8
CHAPTER TWO
LITERATURE REVIEW
Introduction 1.0
This chapter focuses on the literature review from the various sources which includes the books,
magazines, journals, periodical as well as the websites. It entails the review of the analytical
literature, summary of the gaps to be filled.
In this chapter it will describe various concepts particularly to the existing literature and
providing the insights into the relevant existing studies especially in the fields of IT, big data and
the management control systems (Wang, Kung & Byrd, 2016). In this chapter it discusses the
theoretical basis for the study.
2.1 Information technology
The information technology has become omnipresent and it is changing each aspect of
individual’s lives. Additionally, IT has become an integral part especially in the modern
organizations and it has changed on the way many of the organizations processes and operations
(Chen, Chiang & Storey, 2012). Therefore, this is a consensus that the information technology
has a great impact towards the productivity of the organizations.
In the recent decades, the information technology has advanced at a fast pace, and what was hard
to imagine has now become part of every individual live (Chen, Chiang & Storey, 2012). Among
others, is the online shopping, digital marketing, cloud computing, digital communication along
with social networking such as Facebook (Raghupathi & Raghupathi, 2014). To make usage of
the available data many organization have acquired various kinds of IT systems and programs.
2.2 Big data
The data has been a brick to which any organization could blossom. The big data and the
analytics offers various benefits. It has helped in the creation of the various kind of the values,

BIG DATA 9
transparency, expose of the variation as well as the improvement of performance (Russom,
2011). Moreover, it has been found to support the human decision making with the use of the
automated algorithms and innovating new business models, services and the products. It is
evident that with the rapid development of the information technologies for example the cloud
computing, the mobile internet as well as the internet of things there has been all kind of data
which has been generated and accumulated (Ross, Ressia & Sander, 2017). Therefore, this could
present opportunities and unprecedented challenges which could be associated to the available
data.
2.2.1 Definitions and features of the big data.
The big data has been a concept which has been leading the world and it has been taken as storm.
Some of the research regards as a huge set of the data which is possible to analyze by hand or
even through the traditional methods, for example the spreadsheet. A portion of the scholar
thinks that it is a set of the data asset to the organization, which has many values and there is a
lot of benefits which could be generated from using it. It has been changing on the way the
business are performing (Ross, Ressia & Sander, 2017). Many organization are investing in it to
derive the value from their data which have an advantage over the rival firms. There would be a
performance gap which will still grow as more relevant data has been generated, emergence of
new technologies as well as the digital channels which provider a better acquisition and a
delivery mechanism. The big data has a datasets which has sizes which go beyond the abilities of
the traditional as well as the common tools in the business to capture, manage as well as store the
data processes.
2.2.2 Big data and its significance
As more volume of data keeps to grow exponentially, organization have turned to the huge
amounts of the data as well as analytics to form a strategy and decision making (Gunasekaran,

BIG DATA 10
Papadopoulos, Dubey, Wamba, Childe, Hazen and Akter, 2017). The Big Data technologies are
impacting the businesses positively as they are providing the possibility of storing and analyzing
the huge amount of data to unseen patterns, sentiments as well as the customer intelligence
(Gandomi & Haider, 2015). In today world which has been fast changing, it is vital for the
businesses to stay ahead of their peer and at the same time react faster to the changes in the
market, act on the present and future shortcomings. Big data is becoming a significant assets to
many organization in making of decision (Wang, White & Chen, 2015). The Big Data
technologies analyze huge amount data from various sources to offer opportunity to deliver
benefits to organizations. According to Wang, White & Chen, (2015) one of the significant
benefit of the Big Data is the ability of making a wider availability, transparency as well as
visibility to the information to the decision makers in the business. Big data and analytics offers
manager ability to measure and be able to know more about their organization, customers and
market, and be in a position of translating the knowledge (Tesfaye, 2017).
2.2.3 Challenges of Big Data
While there are many benefits which Big Data provides there are also some challenges which
exists and should be addressed to realize the potential of Big Data (Ross, Ressia & Sander,
2017). Some of the challenges are function of the features of Big Data, some are associated to
the existing analysis methods, models and others are through limitation to current data
processing system. For the organization to reap benefits of Big Data and analytics and become
fully, Big Data empowered organization, they need to overcome some of these problems and
challenges. According to Chen, Chiang and Storey, (2012) one of the major problem of Big Data
is the high cost of the infrastructure. Moreover, based on Diesner, (2015), argued that based on
lifecycle of the data the challenges could be grouped as data processes and the management.
Additionally according to Diesner, (2015) also categorized the challenges of the Big Data as the

BIG DATA 11
managerial as well as technological challenges. Moreover, the process challenges which have
been identified by Gandomi & Haider, 2015), have been classified as the technological
challenge. This thus, shows that most of the scholars agree to the fact that these challenges of the
Big Data are major managerial as well as technological.

BIG DATA 12
CHAPTER THREE
RESEARCH DESIGN AND METHODOLOGY
3.0 Introduction
The research was done quantitative. This is because some numerical data was collected in order
to explain phenomena and frequencies sought to enable explanation of meanings, it entails the
research design that was utilize in the research and data analysis.
3.1 Research Design
Descriptive investigations are created to obtain pertinent and precise data concerning the present
level of phenomena. Descriptive design is furthermore aimed to acquire information which is
often analyzed, patterns extracted and compression created (Havakhor, 2016). The researcher
utilize questionnaire which consisted of organized and unstructured questions.
3 .2 Target Population
The population is an entire set of people who have commonly observed characteristics. The
target population interest in this study was compromised of employees working in the financial
organization.
Table 3.1: Target Population
Categories Target population
Management 5
Supervisory staff/ 12
Operational staff 33
TOTAL 50
3.3 Sample and Sampling technique
The researcher used random sampling techniques that assist the researcher to achieve
representation that is desired to various sub-groups in population. Respondents were drawn from
each group randomly to ensure that all the departmental associations were represented in the
sample population (Diesner, 2015).

BIG DATA 13
Table 3.1: Sample Size
Categories Target population
Management 1
Supervisory staff 3
Operational staff 6
TOTAL 10
Source: Author (2017)
3.4 Data Collection Instruments
The researcher used both primary and secondary data, primary data collected through open-
ended and close-ended questionnaires, which present the banking institution, defects noted
corrected. The corrections were included in the questionnaire to enable collection of requisite
data from the employees; the researcher administered the final questionnaire to the respondent,
and because it was appropriate to administer the primary data was supplemented by secondary
data from the available literature relating to the study area.
3.5 Validity and Reliability
Validity is the level which analyzes activities what seemed to be designed to measure. The
validity of instruments is the level of precisely how correctly the information acquired in the
study signify the adjustable. To check for information authenticity within this research the
researcher relied on the professional judgments who commented on simplicity of the tool and
content coverage.
3.6 Data collection procedure
The researcher communicated to the manager to seek authority to access information on
technology they have implemented. After the permission was granted the questionnaires were
hand delivered and they were distributed to other respondents through the assistance of a
research assistant, after which the researcher collected the feedback for analysis.
3.7 Data analysis and presentation
The researcher analyzed the information that was obtained from the research questions. The data
was analyzed using qualitative that is mainly descriptive information and quantitative that is

BIG DATA 14
numeric information procedures (Moniruzzaman & Hossain, 2013). An excel computer packages
was used to analyze the data. This data was presented in frequency tables.

BIG DATA 15
CHAPTER FOUR
DATA ANALYSIS AND PRESENTATION
4.0 Introduction
This chapter presents and discusses the analysis of the presentation and interpretation of the
researcher’s findings to relate to the research objectives. These explained the procedures and
investigate effects of Big data on the performance of the banking institution.
4.1 Response Data
Table 4.1 Response Rate
Response Frequency Percentage
Management staff 4 40%
Operational staff 6 60%
TOTAL 10 100%
From the analysis in Table 4.1 the researcher found out that the management staff in the
organization to be 40% while that of the operational staff was 60%.
Table 4.2: Effects of big data on competitiveness of organization
Response Frequency Percentage
Very large extent 2 20%
Large extent 3 30%
Small extent 1 10%
Very small extent 4 40%
TOTAL 10 100%
Source: Author (2017)

BIG DATA 16
From Table 4.2, the data shows that 20% of the respondents indicated that organizational
competiveness could affect the performance in a large extent, 30% of the respondents indicated
that competitiveness is affected at a large extent, 10% of the respondents indicated its on a small
extent while 10% indicated that organizational competitivenessis affected on a very small extent.
Table 4.3: Management effort to enhance the Big Data
Response Frequency Percentage
Yes 3 75%
No 1 25%
TOTAL 4 100%
Source: Author (2017)
From Table 4.3, the data showed that 75% of the respondents indicated that the management is
doing enough a lot to enhance the Big Data services While 25% of the respondents indicated that
they are the management is not doing enough anything to enhance the improvement of Big Data
technology.
Table 4.4: Focus of Big Data technology to enhance organization performance.
Response Frequency Percentage
Customer care services 1 25%
Media advertisement 0 0%
Publishing of organizations
journals
3 75%
Quality products and services 0 0%
TOTAL 4 100%
Source: Author (2017)
From Table 4.4 , the data showed that 25% of the respondents indicated that the organization use
customer care data to improve their service delivery especially in communication and marketing

BIG DATA 17
tool to ensure customer loyalty while 75% of the respondents indicated that they use the data
from the web, journals as well reports.
Table 4.5: How competition affects performance
Response Frequency(outcome) Percentage
Very large extent 3 75%
Large extent 1 25%
Small extent 0 0%
Very small extent 0 0%
TOTAL 4 100%
Source: Author (2017)
From Table 4.5, data showed that 75% of the respondents indicated that competition can affect
the business to a very large extent while 25% of the respondent said it only affect on a large
extent.

BIG DATA 18
CHAPTER FIVE
SUMMARY, CONCLUSION AND RECOMMENDATION
5.0 introduction
The chapter will summarize the research findings as along with providing an analysis of the
research questions. In the chapter it will provide conclusions as well as the recommendations.
This research will provide an impact of the Big Data to the organization.
5.1 Summary of the findings
The summary will focus on the answers to the research questions which have been raised in the
research.
5.1.1 Potential impact of the big data analytic on the organization.
One of the major impact of the Big Data has been on the organizational change or even the
transformation which is necessary in order to support as well as exploit the big data opportunity.
There would be a need of a new role which is necessary for the creation of the opportunities as
well as the anxiety for the people and the organizations (Kwon, Lee & Shin, 2014). The aspect of
the BI and the data science have various roles and they require different skills and approaches.
Many organization are taking the advantage of the Big Data technologies to be able to collect,
interpret as well as capitalize on the vast amount of the new data. According to the review it has
highlighted that the Big Data would be harnessed in order to understand the consumers,
improvement of the healthcare as well as cut the organization operational costs.
5.1.2 How the data and data analytic enhance the performance of the organization.
The data analytic are the business intelligence technologies which are grounded in the data
mining as well as the statistical analysis. This tool relies on the mature commercial technology of
the relational DBMS, the data warehouse as well as OLAP (LaValle, Lesser, Shockley, Hopkins
& Kruschwitz, 2011). This technology has been a revolutionary new platform which the large
scale parallel data could be accessed (McAfee, Brynjolfsson & Davenport, 2012). This tool has
been used by many organization to study on the large volume of the data which patterns could be
drawn that could help the organization to make decision and to offer it competitive advantage of
the other firms. Additionally, some of the technique has been used to study the dynamic nature of
the social network (Lee, 2017).

BIG DATA 19
5.2 conclusion
Big Data is changing to the way organizations performs. It has led to more volume as well as
higher variety along with the veracity of the data. However, the business have encountered
numerous obstacles. However, although there have been urgent need for the business to respond
to the unstable environment of the business timely, the business need to have numerous
capabilities and the capitals. Without overcoming the aspects of the infrastructure, the
technological as well as the managerial challenges with the Big Data technologies, the business
will not realize these benefits. Therefore, to enable an organization which is Big Data enabled
the changes in the business are inevitable. This thus means that the Big Data could impact the
organizations in numerous ways especially to the way they operate and control their processes.
5.3 Recommendations
For the organization to fully make use of the Big Data technology they need to first identify on
their market niche so that they can be able to know the kind of technology they want. Moreover,
they need to invest on the various infrastructure which should be dependent on what they are
willing to spend as a business. Organization should not spend on what they are not able to afford
to loss since the cost of the operation cost increase and lender them bankrupt. Additionally, there
is need to look at the current trends in the market in regards to the technologies and adopt the one
most useful to the business.
5.4 suggestions for the further research.
In this research the findings seems to be conclusive, but there are areas which needs further
investigation such as the value of the big data analytics tools as well as the developing theories to
have a better understanding the circumstances are under which the information technology
resource could be translated into the improvement of the performances.
5.5 limitations.
Notwithstanding the contributions of this research, there are various limitations. In this research
it has been undertaken in one industry which is financial sector there is need for further research
to other industries since it involved a lot of generalization of the variables. Another constraint
was funding, this made the research not to be extensive since the research focused only few
institution. A large sample size would have provided a more comprehensive data analysis.

BIG DATA 20
6. References
Agrawal, D., Das, S., & El Abbadi, A. (2011, March). Big data and cloud computing: current
state and future opportunities. In Proceedings of the 14th International Conference on
Extending Database Technology (pp. 530-533). ACM.
Braganza, A., Brooks, L., Nepelski, D., Ali, M., & Moro, R. (2017). Resource management in
big data initiatives: Processes and dynamic capabilities. Journal of Business Research,
70, pp.328-337.
Chen, H., Chiang, R.H., & Storey, V.C. (2012). Business intelligence and analytics: From big
data to big impact. MIS quarterly, 36(4).
Diesner, J. (2015). Small decisions with big impact on data analytics. Big Data & Society, 2(2),
p.2053951715617185.
Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics.
International Journal of Information Management, 35(2), 137-144.
George, G., Haas, M. R., & Pentland, A. (2014). Big data and management. Academy of
Management Journal, 57(2), 321-326.
Gunasekaran, A., Papadopoulos, T., Dubey, R., Wamba, S. F., Childe, S. J., Hazen, B., & Akter,
S. (2017). Big data and predictive analytics for supply chain and organizational
performance. Journal of Business Research, 70, 308-317.
Havakhor, T. (2016). Big Data and Organizational Impacts: A Study of Big Data Ventures
(Doctoral dissertation, University of Arkansas).
Hussain, A., & Roy, A. (2016). The emerging era of Big Data Analytics.
Kwon, O., Lee, N., & Shin, B. (2014). Data quality management, data usage experience and
acquisition intention of big data analytics. International Journal of Information
Management, 34(3), 387-394.
LaValle, S., Lesser, E., Shockley, R., Hopkins, M. S., & Kruschwitz, N. (2011). Big data,
analytics and the path from insights to value. MIT sloan management review, 52(2), 21.
Lee, I. (2017). Big data: Dimensions, evolution, impacts, and challenges. Business Horizons,
60(3), 293-303.
McAfee, A., Brynjolfsson, E., & Davenport, T. H. (2012). Big data: the management revolution.
Harvard business review, 90(10), 60-68.

BIG DATA 21
Moniruzzaman, A. B. M., & Hossain, S. A. (2013). Nosql database: New era of databases for big
data analytics-classification, characteristics and comparison. arXiv preprint
arXiv:1307.0191.
Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: promise and
potential. Health information science and systems, 2(1), 3.
Ross, P. K., Ressia, S., & Sander, E. J. (2017). Work in the 21st Century: How Do I Log on?.
Russom, P. (2011). Big data analytics. TDWI best practices report, fourth quarter, 19, 40.
Tesfaye, B. (2017). What is the influence or Big Data and Analytics on Management Control
System.
Waller, M. A., & Fawcett, S. E. (2013). Data science, predictive analytics, and big data: a
revolution that will transform supply chain design and management. Journal of Business
Logistics, 34(2), 77-84.
Wang, X., White, L., & Chen, X. (2015). Big data research for the knowledge economy: past,
present, and future. Industrial Management & Data Systems, 115(9).
Wang, Y., Kung, L., & Byrd, T. A. (2016). Big data analytics: Understanding its capabilities and
potential benefits for healthcare organizations. Technological Forecasting and Social
Change.