Research Report: Big Data Analytics in Business Intelligence

This report explores the intersection of Big Data (BD) and Business Intelligence (BI), examining their impact on job markets and competency demands. The research investigates the background of BD and BI, their respective competencies, and a comparison of their similarities and differences. The methodology involves a content analysis of job advertisements using text mining techniques, focusing on data collection from online sources and data analysis via singular value decomposition. The report aims to determine which domain, BD or BI, offers more job opportunities and to assess the demand for BI and BD professionals. The findings are expected to provide insights into the evolving landscape of data analytics and its implications for businesses and professionals. The research also considers ethical factors and limitations, such as the reliance on job advertisements as a proxy for demand.

Running head: BIG DATA ANALYTICS IN BUSINESS INTELLIGENCE
Big Data Analytics in Business Intelligence
Name of the Student:
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Table of Contents
Chapter 1: Introduction..............................................................................................................2
1.1 Background of the Research........................................................................................2
1.2 Research Objective......................................................................................................2
1.3 Topic of Research........................................................................................................2
1.4 Research Structure.......................................................................................................3
Chapter 2: Literature Review.....................................................................................................4
2.1 Business Intelligence and Big Data.............................................................................4
2.2 Competency for the BI................................................................................................4
2.3 Competency for the BD...............................................................................................5
2.4 Comparison of BD and BI...........................................................................................6
Chapter 3: Research Methodology.............................................................................................7
3.1 Schedule of research approach....................................................................................7
3.2 Equipment to conduct research...................................................................................7
3.2.1 Data Collection..........................................................................................................7
3.2.3 Sample Size...............................................................................................................8
3.2.3 Data Analysis............................................................................................................8
Chapter 4: Conclusion................................................................................................................9
Reference..................................................................................................................................10

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Chapter 1: Introduction
1.1 Background of the Research
Big data and business intelligence is one of the most discussed topics in research and
practice whether it be in academics or business (Buhl et al 2013). Big data simply indicates
the data set that are complicated and large in size which is difficult to process using the
traditional storage and technologies. Big data has appeared in 2011 in the part of Business
intelligence and analytics. This helps to present the odd and new data source for example
social media, new technologies like visualisation and predictive analytics and the
combination of very different skills for an example a data scientist.
1.2 Research Objective
The aim of the paper is to find out which domain between Big Data (BD) and Business
Intelligence (BI), has offered the job vacancies effectively. This will show the comparison
between these two in terms of the impact on creating job vacancies. Secondly, this paper aims
to find out the competitors demand while BD and BI is emerging and growing at a high pace
in the modern technological era. Finally, the paper wish to compare both the BD and BI. In
simple words, it wants to find out the similarities and dissimilarities between these two which
will show the advantage of one over the other and the advantage of merging to each other.
1.3 Topic of Research
The research topic that are extracted from the research objective are mentioned below:
Topic 1: Between business intelligence and big data which one have offered more jobs to the
new generation?
Topic 2: Is there any demand for the competency for the BI professionals?
Topic 3: Is there any demand for the competency for the BD professionals?

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Topic 4: What are the similarities and dissimilarities between BI and BD jobs?
1.4 Research Structure
The structure of the research starts from an abstract which provides the summary of the
overview of the paper. The major chapter of the paper are the introduction, background of the
research, discussion of the research topic, literature review, justification and outcome of the
research, methodology, limitation of the research, findings from the research, future
perspective of the research. The research methodology incorporates the discussion of data
collection, sampling and the data analysis methods which will be used to conduct the
research.

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Chapter 2: Literature Review
The RBV of a firm is very useful in the evaluation of implementing BD or BI to
generate business value by identifying the required resources and expertise that can create
competitive advantage in the market.
2.1 Business Intelligence and Big Data
“Business Intelligence”, the term is coined by Howard Dresner in 1989 which replicate a
huge number of concepts and business methods which helps to make improvement in
decisions making for the business depending on the facts and data.
“Big Data”, the term was in trend from 1990s. This refers to the large data set that were
not fitting in to the storage. Later in 2001, Dough Laney renamed this as “the 3Vs” which
stands for variety, volume and velocity and used in the business purposes. Social media like
Facebook which does their business depending on the internet has used the big data where
they have applied advance data mining and machine learning technique. Data warehouse is a
system that can be used for data analysis.
The difference between the BI and BD is that the BI focuses on the traditional use of
metrics which helps to measure the business performance depending on the past, on the other
hand, big data explores, make discoveries and predictions. Big data works in such a way
where a human cannot consider the validation of critical questions.
2.2 Competency for the BI
There is not enough papers that studies the competency of individual BI. So, the overview
of the requirements of competency of individual BI is extracted by going through the
capability models and literature review of BI and reports. The focus of research and the
practice was on the development of the maturity of BI. Industry has originated the models
which incorporates the TDWI Business Intelligence Maturity Model, Gartner’s Maturity

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Model for Business Intelligence and Performance Management (Shaaban et. al. 2017),
Gartner’s Magic Quadrant for Business Intelligence Platforms, and Logica’s
Capability/Maturity Model (Barra and Ladeira 2017). These all industrial maturity models
focuses on the capabilities of technology which should be provided by the BI platforms.
Except these IT capabilities, academic models gives the overview of BI strategies like IT-
business alignment and planning of architecture. In an organisational level, these are enough
to be engaged in BI. These are helpful in developing the competency of individual BI. A
report published in 2011 says that trend in industry raises concern regarding the slow pace in
offering the BI courses and programmes to the students. There are some system software
which is helpful for analytical tools. The report also argues on the topic that a deep
knowledge of business and communication skills are important and very much required.
2.3 Competency for the BD
An article of Harvard Business Review presents the data scientists as the data hacker and
effective trustworthy analyst communicator adviser and also describes the job as “the sexiest
job of the 21st century” (Debortoli, Müller and vom Brocke 2014). Facebook has created the
first ever team of data scientist who wrote the processing pipeline on multi-tasking analytical
software Python, designed few statistical tests and performed the regression using R where
they have developed some algorithms with the help of Hadoop to communicate with the
members of organisations (Warren and Manos 2017). The data scientists were even described
as the hybrid of computer scientist and statistician and it is also said that it is not possible to
separate the data processing from the knowledge domain or the analysis. Hence, BD
professionals must have to carry the industrial knowledge just to communicate to others with
the sense of statistical analysis.

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2.4 Comparison of BD and BI
In traditional terms of business, the team representing BI are responsible for the internal
consulting organisations, core of excellence and the department of IT. It is technological
process for analysing data. In this system prepare run quires, dashboard. In this places, they
outsource the knowledge to the executives through managers by providing the reports that
contains the information needs that are well-defined, organised and stable (Nofal and Yusof
2016.). On the other hand, the BD is lagging behind with the predefined questions and they
are the much more experimental by nature than the BI. For this reason, the BD professionals
must have to make themselves organise so that they make themselves more close to the
process and the products of the organisations (Warren and Manos 2017).

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Chapter 3: Research Methodology
The literature has provided the insights of the competency of BI and BD. This makes the
research not be limited in the empirical data. This leads the researcher to study the
competencies of professionals of BI and BD.
3.1 Schedule of research approach
The research methodology that is going to be used in the research, will follow an
automated content analysis of advertisement of job by the use of text mining technique which
is also known as latent semantic analysis. This is nothing but a quantitative method to analyse
the qualitative data. This technique take out the pattern of used words in advertisements and
the meaning by the use of statistical calculations depending on the way the words appear or
do not appear that determines the meaning of the word. This technique follows the style of
explanatory factor analysis where LSA uses the matrix operation which is known as singular
value decomposition (SVD). IS discipline that conducts quantitative content analysis of
academic papers has given the priority to the LSA.
3.2 Equipment to conduct research
3.2.1 Data Collection
The data will be collected from the online sources that conducts the recruitment all over
the world through the websites like monsters.com, the job advertisements from the various
countries where BI and BD is trending as a great job profile. The advertisements that uses the
term “business intelligence” or “big data”. Then a data cleaning process will be followed to
remove the irrelevant data. The terms that are irrelevant like “and”, “or”, “then”, “salary” and
“apply” will be removed. After data cleaning, the terms will be divided in two sets, one set is
for BI jobs and the other one is BD jobs.

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3.2.3 Sample Size
The research initially looking forward to collect a total number of 6000 BI related and
3000 BD related job ads.
3.2.3 Data Analysis
The data analysis will perform the singular value decomposition method using R. This
will generate scree plots and Kaiser-Harris criterion. There will be tested a number of
dimensionalities including several factors and for each factor SVD will be performed to
calculate term and documents.

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Chapter 4: Conclusion
There for it can be concluded that the research will be performed by considering the
ethical factors. All the information from the private websites will be collected with proper
permissions and will not be used in any other area except for the study purpose. There are
several issues that are limited in nature. As the research will be conducted on the
advertisements that have been published in the fixed range of time. The data analysis
considers the advertisements as a proxy of demand for the human resources which is not
always true.
3.1

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Reference
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Buhl, H.U., Röglinger, M., Moser, F. and Heidemann, J., 2013. Big data.
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