Expert answer:Research Paper on Big Data and Data Analytics
Solved by verified expert:Topic Title: Strategies to Implement and Integrate Big Data and Data Analytics to Improve Business Decisions (The research should answer the question what strategies should business use in leveraging big data and data analytics to improve business decisions?) ** This paper is the continuation of first paper, I am attaching bellow. The Methodology paper is a research paper about your selected research method and process. This paper must include the reasons and justification for approach, a minimum of eight (8) peer-reviewed references, and follow the section outline below. Method Research Design Describe and define the anticipated research approach or strategy to be used and how this approach is appropriate for this research Participants Describe the anticipated sample population (number, gender, age, socio-economics, etc.) including how you will obtain permission and consent Instrumentation Describe any instruments you anticipate using to collect data Procedure Provide the detail about how you anticipate conducting the research Data Processing and Analysis Explain, in detail, how you anticipate processing and analyzing collected data Summary The paper should contain at least 7-8 pages of content not count title page, table page and a reference page. * Table of contents, Introduction, conclusion and sub headings are mandatory * APA Format should follow all APA rules (citations, quotations, references) *Follow the Template * No Plagiarism
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Running head: USING BIG DATA AND DATA ANALYTICS IN BUSINESS DECISIONS
Strategies to Implement and Integrate Big Data and Data Analytics to Improve Business
Decisions
1
USING BIG DATA AND DATA ANALYTICS IN BUSINESS DECISIONS
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Table of Contents
Abstract……………………………………………………………………………………………3
Project Overview………………………………………………………………………………….4
Introduction……………………………………………………………………………………….5
Problem Statement…………………………………………………………………………………7
Research Question(s)………………………………………………………………………………8
Rationale………………………………………………………………………………………….9
Stakeholders Involved……………………………………………………………………………10
Conclusion……………………………………………………………………………………….10
References……………………………………………………………………………………….11
USING BIG DATA AND DATA ANALYTICS IN BUSINESS DECISIONS
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Abstract
The idea of creation of business value by big data and data analytics is not new; however,
when such data is effectively used has become the basis of competition. Businesses have always
had the desire to derive market insights from information contained in the big data in order to
make smarter, better, fact-based, real time decisions. Hence it is this demand from businesses for
in-depth and detailed information that has propelled the tremendous growth of big data and data
analytics tools as well as platforms. The frontiers in this paradigm shift now include big data
both internal and external of the enterprise, including unstructured and structured data, mobile
and online data, as well as machine data to supplement the data obtained from the organization
and subsequently provide the basis for historical view as well as forward-looking (predictive and
statistical) view. Big Data and data analytics have been evidently found to significantly
influence decision making in hiring and marketing fields. As a result, hiring and marketing
decisions have currently undergone a metamorphosis from previous qualitative measures towards
a quantitative driven-measure that is science-based. Thus, big data and data analytics have been
proven to play an imperative role in shaping hiring and marketing decisions and if appropriately
utilized they are likely significantly improve the business performance.
USING BIG DATA AND DATA ANALYTICS IN BUSINESS DECISIONS
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Project Overview
This research project is broad and consists of various sections which cover varied details
relevant to the research. The research project covers the topic on the strategies that can be
adopted to implement and integrate Big Data and data analytics to improve business decisions
(particularly hiring decision and marketing decision). The research project consists of the
abstract, project overview, introduction, problem statement, research questions, rationale and
stakeholders involved. Each of the listed section covers varied details related to the research
project. For instance, the abstract presents a summary of what is covered in the entire research
project in order to give a glimpse of the contents at first glance. The project overview section
gives a breakdown of what is contained in the research project, whereas the introduction
provides introductory details of the research topic. However, the problem statement section
delves into providing insights into the problem presented by the phenomenon under investigation
(Couldry & Turow, 2014). The research questions section outlines the questions that ought to be
answered by the results obtained from this research project. Furthermore, the rationale section
provides a justification of why it is necessary to carry out the research and why the research
results will be important. Finally, the section of stakeholders involved gives a glimpse of all
those who are involved in topic of research; and the conclusion presents the concluding remarks.
Introduction
It is envisaged that big data and data analytics will lead to fundamental change in the
manner businesses operate and compete. As a result, businesses that have invested in and
successfully derived value from data analytics are undoubtedly distinctively advantaged over
their competitors. Thus, depending on how relevant big data is generated and utilized, a
USING BIG DATA AND DATA ANALYTICS IN BUSINESS DECISIONS
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performance gap anticipated to continue to grow between businesses relative to how they use
their data as well as data from outside. This assertion is underscored by the changing trends in
emerging technologies in conjunction with digital channels that play an imperative role in
offering better mechanisms of acquisition and delivery, as well as the technologies that enable
easier, faster data analysis techniques which continue to develop (Kimble & Milolidakis, 2015).
However, while there has been unprecedented rate in which the growth of the ability of capturing
and storing vast amounts of data, the technical capacity of aggregating and analyzing these
disparate information volumes has lagged behind and has being catching up slowly. Therefore,
the specific strategies that can be used in the implementation and integration of big data and data
analytics towards improvement of business decisions are discussed below:
Choosing the right data
It is undeniable that the universe of data analytics and modeling has undergone vast
changes over the past few years. There has also being rapid growth of the volume of information,
while opportunities for the expansion of insights through combination of data have still
accelerated (Couldry & Turow, 2014). Bigger and better data either obtained from the business
alone or in combination with external data give companies both more granular and panoramic
views of the business environment. As a result, the ability of previously invisible insights to be
seen may play an imperative role in improving operations, strategy, and customer experience.
Building models for prediction and optimization of business outcomes
It is important to emphasize the essence of data, but improvement of performance and
achieving competitive advantage are obtained from data analytics models that have the potential
of allowing managers in predicting and optimizing business outcomes. However, it imperative to
USING BIG DATA AND DATA ANALYTICS IN BUSINESS DECISIONS
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note that, the most cost effective and more important approach to building data analytics models
do not begin with the data, but with business opportunity identification and determination of how
performance will be improved by the model (Arthur, 2013).
Transforming the business capabilities
This is the most important strategy of big data and data analytics implementation and
integration into improvement of business decisions, and it is effectively actualized by matching
between an existing culture of the organization and capabilities as well as emerging tactics to
successfully exploit business data analytics. The business decision makers as well as those on the
front lines in different business departments must be involved through a collaborative and
consultative approach in order to ensure the business is transformed and aligned with analytics
results in order to achieve the desired outcomes (Couldry & Turow, 2014).
Using Big Data and Data Analytics to Improve Hiring Decisions
Big data and data analytics is without any doubt the driving force that behind today’s
business strategy, and management of human resources, especially hiring of new employees has
not been an exception (Kimble & Milolidakis, 2015). It has given recruiters in businesses the
tools needed to make better hiring decisions, and is changing the manner in which organizations
boost employee engagement, measure performance, analyze talent needs, and prioritize training.
As a result, today there has been increased accessibility to a data gold mine by HR departments,
an unprecedented amount of data: trends, intelligence, insights, and future-casting. Thus, there
are specific applications through which strategies for implementation and integration of big data
and data analytics can be used towards improvement of hiring decisions (Linoff & Berry, 2013).
USING BIG DATA AND DATA ANALYTICS IN BUSINESS DECISIONS
7
Tuning of the hiring policies plays an imperative role in ensuring that hiring decisions are
significantly improved in order to allow the best team of employees to be recruited and hired.
Data available from the internal systems of a business as well as external sources including
public transportation, demographic, social media, and compensation surveys has the potential of
revealing patterns that are helpful to a company in determining where to hire employees from
and at what cost (Saxena & Srinivasan, 2012). Big data helps recruiters in making decision on
focused recruitment marketing. For instance, volumes of data are captured by online job listing
sites, and that data has the potential of giving insights into what has the possibility of eliciting the
best quantitative and qualitative response. Through this approach informed by the hiring decision
motivated by business data analytics, it is possible to attract the best pool of talented employment
candidates.
Using Big Data and Data Analytics to Improve Marketing Decisions
Furthermore, big data and data analytics can be used to improve marketing decisions in a
business. This is because marketing is dependent on numbers, and ‘Big Data’ ensures that there
is high-velocity, high-volume, and high-variety information. These assets demand innovative,
cost-effective forms of information processing in order to ensure that there is enhance insight as
well as improved marketing decision making (Banasiewicz, 2013). These characteristic features
are collectively known as the 3 V’s of ‘Big Data’; velocity, volume, as well as variety.
Problem Statement
Over the recent past it is undeniable that the term ‘Big Data’ has pervasively infiltrated
recruitment and hiring as well as marketing circles; eliciting excitement in some quarters, anxiety
and panic in others. Anecdotally, a considerable number of those in human resource management
USING BIG DATA AND DATA ANALYTICS IN BUSINESS DECISIONS
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and marketing fields have some understanding, even though not sufficient about ‘Big Data’
meaning to some extent they make informed decisions based on big data and data analytics.
However, to some businesses it seems complex, inaccessible and in realm of elusiveness,
meaning it is out of reach for them. But the developments recently taking place in both human
resource management and marketing landscapes are envisaged to overhaul everything; thus,
everyone is in a rush to ensure the implementation of new data-centric hiring and marketing
paradigm, where quantitative data is the basis decisions as opposed to the conventional
qualitative assessments, such as gut-feeling and intuition (Chen & Chiang, 2012). Hiring and
marketing decisions are rapidly shifting from the traditional practices and embracing or
incorporating the use of big data and data analytics. Therefore, considering the shifting grounds
it is important to acknowledge the challenge faced by many businesses as they risk being
rendered irrelevant if they do not embrace big data and data analytics (Lusch & Vargo, 2010).
Research Questions
In order to ensure that the research is explicitly carried out, there should be some research
questions which the results should strive to answer. The research questions are as follows:
1. Is Big Data and data analytics essential in improving business decisions?
2. What are the strategies to implement and integrate Big Data and data analytics to improve
business hiring decisions?
3. What are the strategies to implement and integrate Big Data and data analytics to improve
business marketing decisions?
4. To what extent have businesses adopted strategies to implement and integrate Big Data
and data analytics to improve hiring and marketing decisions?
USING BIG DATA AND DATA ANALYTICS IN BUSINESS DECISIONS
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Rationale
The rationale behind this research is that the results are envisaged to affirm the role of big
data and data analytics in improving hiring and marketing decisions in businesses. For instance,
in order to realize the benefits of big data and data analytics, appropriate strategies for their
implementation and integration must be adopted in order to ensure improved business decisions
is achieved. This means that it is critical for the business managements to possess the
prerequisite requirements to ensure transformation of the organization is carried out for better
decisions to actually be yielded from the data and models (Couldry & Turow, 2014). These
competencies are underpinned in two important features including a clear strategy of using the
big data and data analytics for competition as well as ensuring that right technology capabilities
and architecture are deployed. Furthermore, as important, the desired business impact derived
from a clear vision must be put in place as a strategy of shaping the integrated approach to
sourcing of data, model building, as well as transformation of the organization. In addition, the
marketing landscape can be significantly influenced by ‘Big Data’, subsequently leading to a
shift in the process of marketing decision making. This may also lead to changes in the manner
in which small businesses are envisaged to undertake marketing activities, changes in the
competitive advantage landscape, changes in the flow of communication between customers and
organizations using social media, as well as the advent of marketing that is precisely targeted in
addition to the long-tail mining for the purpose of exploration of untapped segments. These
effects or ways in which ‘Big Data’ influence marketing decisions are destined towards having a
significant impact on marketing as well as forcing an evolution from conventional marketing
tactics, heavily based on qualitative measures toward the new data-centric quantitative paradigm.
Stakeholders Involved
USING BIG DATA AND DATA ANALYTICS IN BUSINESS DECISIONS
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In the process of adopting strategies to implement and integrate Big Data and data
analytics to improve business hiring and marketing decisions various shareholders are involved.
For instance, there are three main departments which must be involved including the IT
department, HR department and Marketing department. This means that staff in those
departments, especially those that have power to make decisions at managerial or departmental
head level must be involved. In addition, the managements of respective businesses are also key
shareholders mainly because they are the ultimate determiners of which hiring and marketing
decisions to be pursued or implemented (Linoff & Berry, 2013). Furthermore, in cases where
external data is needed third party vendors may also be included as shareholders if they are
involved in providing the external data, but also, they can be exempted if the external is sourced
by the respective businesses.
Conclusion
In conclusion, Big Data and data analytics have been evidently found to significantly
influence decision making in hiring and marketing fields. As a result, hiring and marketing
decisions have currently undergone a metamorphosis from previous qualitative measures towards
a quantitative driven-measure that is science-based. Thus, big data and data analytics have been
proven to play an imperative role in shaping hiring and marketing decisions and if appropriately
utilized they are likely significantly improve the business performance.
USING BIG DATA AND DATA ANALYTICS IN BUSINESS DECISIONS
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References
Arthur, L. (2013). ‘Big Data’ Marketing: Engage Your Customers More Effectively and Drive
Value. Hoboken, NJ: John Wiley & Sons.
Banasiewicz, A. D. (2013). Marketing Database Analytics: Transforming Data for Competitive
Advantage, New York, NY: Routledge.
Chen, H. & Chiang, R. H. L. (2012). Business Intelligence and Analytics: From ‘Big Data’ to
Big Impact. MIS quarterly, 36 (4), 1165-1188.
Couldry, N. & Turow, J. (2014). Advertising, Big Data, and the Clearance of the Public Realm:
Marketers’ New Approaches to the Content Subsidy. International Journal of
Communication, 8 (3), 1710-1726.
Kimble, C. & Milolidakis, G. (2015). Big Data and Business Intelligence: Debunking the
Myths. Global Business and Organizational Excellence, 35 (1), 23-34.
Linoff, G. S. & Berry, M. J. (2013). Data mining techniques: for marketing, sales, and customer
relationship management. Hoboken, NJ: John Wiley & Sons.
Lusch, R. F. & Vargo, S. L. (2010). Service, value networks and learning. Journal of the
Academy of Marketing Science, 38 (1), 19-31.
Saxena, R. & Srinivasan, A. (2012). Business Analytics: A Practitioner’s Guide. International
Series in Operations Research & Management Science. Berlin: Springer.
Running head: Research Title
Strategies to Implement and Integrate Big Data and Data Analytics to Improve Business
Decisions
1
Research Title
2
Table of contents
Research Design………………………………………………………………….3
Participants…………………………………………………………………………..5
Instrumentation……………………………………………………………………….6
Procedure…………………………………………………………………………………7
Data Processing and Analysis……………………………………………………………….9
Summary………………………………………………………………………………..10
References………………………………………………………………………………11
Research Title
3
Methodology
The methodology section is a major section of your research paper and, as such, is
preceded by a level one heading formatted in accordance with the requirements in the
Publication Manual entitled “Methodology”. The methodology section is expected to be
extensive and detailed. This section is written in the past tense. An appropriately detailed
research methodology discussion allows the reader to judge the scope and soundness of your
research. This section must provide specifics regarding each of the research approaches (i.e.,
quantitative, qualitative, triangulation or action research) that you actually pursued. The
methodology should provide sufficient detail to make it readily apparent to the reader how each
of the selected research approaches contributed to answering your research question(s) and
solving your stated problem. Refer to the Publication Manual for additional guidance regarding
the content of the methodology section.
Research Title
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