Introduction to Business Analytics Assessment 2022

Running head: INTRODUCTION TO BUSINESS ANALYTICS
Introduction to Business Analytics
Name of the Student
Name of the University
Author Note

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INTRODUCTION TO BUSINESS ANALYTICS
Table of Contents
Part A: Case study Analysis............................................................................................................2
Big data and Art...........................................................................................................................2
Amsterdam Fire department case study.......................................................................................3
Part B: The role of analytics in solving business problems.............................................................4
Part C: Sourcing analytics professionals.........................................................................................6
1-Part............................................................................................................................................6
Part 2............................................................................................................................................7
Bibliography....................................................................................................................................9

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Part A: Case study Analysis
This part of the assessment focuses on evaluating the case studies based on the
implemented technologies. It is very much essential for the organization to implement proper
data analytics technology so that it can offer better customer services. With the use of proper
technology it becomes easy to increase the efficiency of the organization.
Big data and Art
In the case study it can be observed that big data has been introduced for the purpose of
enhancing the business performance. In order to enhance the art and design it is essential to use
appropriate technology that will be capable of providing better designs. The industry in which
the big data concept is used is IBM. The problem that was faced within the organization was
with removing the needs of the human. There are several areas that need human interaction.
Without proper support from human it will become very difficult to meet the needs of the
business. Thus with the implementation of augmentation, it is expected that the overall business
objective can be meet. In order to carry out the designs effectively it is important use proper
technology that will be capable of resolving the issues in the organization. In order to enhance
the way art and design is executed it is important to implement the new technology
augmentation. With the help of augmentation it will become easy to design more attractive as
culture. For the purpose of creating Gaudi’s work, the organization took initiative to implement
proper resolution so that they can meet the needs he customer. The main objective is to manage
the overall performance of the system so that they work on providing proper design towards the
customers.

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However with the use of big data analytics in business there are certain challenges that
are likely to impact the performance of the business. These mainly involve security provided
towards the big data and organizational resistance. Thus there is a need to have proper analysis
of the technology for managing the overall performance. With the use of proper analytical tools
and technologies it will become easy to provide proper support towards the customers.
Implementation of proper data analytics will enhance the business performance as this has the
potential to meet the target of the organization. Efficient technologies are needed for enhancing
the overall performance.
Amsterdam Fire department case study
The objective of analyzing the case study is to identify the issue that is needed to be
solved. Amsterdam fire department has a data consultancy sector that uses linked data in
firefighting. The concept behind using this system is that it offers an efficient way of collecting
wide amount of data with the use of technology such as internet of things sensors that are
attached with the file engineers and pumps. However it has been observed that the concept also
applies on making the data more vulnerable towards the public. It can be stated that with the use
of valuable data sets and enhanced technology it becomes easy to create new applications that
can prevent individuals from getting attacked from such incidents.
In the case study it has been observed that different technologies are used for the purpose
of providing quick access to words the service. This was considered to be one of the most vital
steps for the purpose of organizing the data sets through which predictions can be made for
preventing major issues. Apart from this Future predictive modeling can be used for a proper
system for assessing the risk profile. The data that you’re connected with the use of technologies
can be used to further for the purpose of preparing models for assessing risk. Earlier Amsterdam

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fire department faced issues with managing the data sets and for collecting successfully the
information. Thus there is a need to overcome these issues. In order to overcome this issue it is
important to have effective models that will be capable of evaluating on data sets. The effective
data will be capable of meeting the needs of the organization and will also ensure that the
technology is capable of providing a better service towards the customers.
Part B: The role of analytics in solving business problems
Analytics are used for the purpose of providing efficient support towards the
organization. The two different types of analytics are descriptive analytics and predictive
analytics.
Descriptive analytics: This offers efficient visualization and managing the summary
statistics bases on the past data. Descriptive analyses helps in describing the use of a wide range
of historic data for the purpose of drawing of efficient conclusion. This takes raw data and parts
that is data for drawing a meaningful conclusion. This is considered as an important component
for providing better performance. This also helps in making efficient decision based on the
historical data. With the help of a descriptive analysis it becomes easy to draw conclusions. This
also helps in enhancing the business performance.
Descriptive analysis is a useful in different fields. With the help of proper descriptive
analysis it becomes easy to achieve the information. This helps in developing the report on return
on investment by explaining the performance. Descriptive analysis it becomes easy to identify
the gaps within the business process. With the use of efficient analysis it becomes easy to
manage the data resources.

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For example: tracking the assessment and assignment grades with the descriptive analysis
is one of the most efficient examples. The descriptive analysis has gained huge importance in the
field of education as this helps in enhancing the business process. The past records of the
students are essential for providing grades on an overall basis.
Predictive analytics: Predictive analysis is one of the data analytics components that are
used for the purposes of determining the future outcomes on the basis of historical data. The
science that is associated with predictive analysis is that it helps in generating future associated
with significant degree of precision. Predictive analytics helps in looking into the future more
accurately and offers reliable tools towards the users. This helps the retailers to find different
ways for saving and earning money. It has been observed that retailers tends to use predictive
models for the purpose of forecasting the inventory please also helps finishing the shipping
schedule and helps in maximizing the sales. The major benefits that are offered with the use of
predictive analytics in day to day life is that it improves the overall efficiency in the production,
helps in gaining advantages from the competitor, reduces the chances of race and heels in
meeting the consumers’ expectations.
For example: with the help of predictive analysis it becomes easy to identify the customer
is there that are likely to abandon a service or product. Let’s take an example that includes
implementing predictive Analytics model in the photo studio. This system is designed in such a
way that it can identify a customer that whether the person is going to renew the membership or
can we draw the membership. In order to identify these it is important to analyze the past data. If
the customer tends to continue the membership then it is important to offer incentives skills.
These reveal help in attracting the customers more.

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Part C: Sourcing analytics professionals
1-Part
In the case study one, data visualization analyst the analytics method that is selected is
descriptive method. The main reason behind selecting descriptive method is that it helps in
enhancing the way data sets are managed. The roles of data visualization include making
complex data more accessible towards the users. This ensures that all the past data are analyzed
properly for providing better efficiency towards the collected data sets. With the help of data
visualization it becomes easy for the data analyst to gain proper control over the data sets.
Business analyst focuses on analyzing the business environment and the data sets. The
main objective of business analyst is that it helps the business implementation technology so that
it becomes easy to organize the communication that takes place within the business partners.
This focuses on certain actions that are planning and monitoring, organizing the requirements,
analyzing the requirements and assisting the business the case. It is important to deliver the
requirements efficiently so that all the needs of the business can be evaluated properly.
Predictive data analytics is used within the business analytics. These helps in offering precise set
of data. Predictive analytics offers proper statistical modeling and machine learning on the data.
Analytics that is used in the role of data scientists is predictive analytics. They allow the
organization to manage the overall data sets.
Data scientists are responsible for managing the math’s and statistic data for efficient
execution. Analytics that is needed for data scientist is automated analytics. With the help of
automatic or prescriptive data analytics it will become easy to manage the overall performance.
Automated data analytics is referred to the practice that is used for the purpose of providing

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proper support towards the computer system. With the help of data analytics it becomes easy to
evaluate the data sets. Hence it can be stated that with the use of automated you data analytics
the scientists will be capable of evaluating data sets more efficiently.
Analytic translators are responsible for translating the data architect. This helps in
working on the knowledge associated with artificial intelligence and analytics. With the
advanced use of the technology it becomes easy to manage the data sets. Analytic translated our
usage and predictive analytic methods for analyzing the data sets.
Part 2
The aim of this part is to offer proper data analytics roles for the case studies so that it
becomes easy to enhance the performance. The first part of the assessment focuses on evaluating
2 case studies that are big data and art and the Amsterdam fire department. After analyzing the
case studies it can be stated that there is a lack of implementation of proper technologies within
both the case studies. Thus it can be stated that with the use of proper data analysis it will
become easy to enhance the business processes. In the first case study of big data and art, it can
be stated that data visualization analyst is needed. Data analyst helps in providing deep
understanding on the requirements that are needed for managing the overall performance of the
business. With deep understanding it becomes easy to meet the objective of the business. The
main reason behind stating these is that it helps in providing proper knowledge about the data
that are needed for successfully executing the organization. This helps in using data
virtualization and offers better access towards the art field. Data analyst needs to be careful while
managing the data sets for the organization.

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With the use of data analyst it becomes easy to provide proper service towards the art
field. From the case study of Amsterdam fire department it can be stated that due to improper
controlling over the business data it became very difficult to organize the data sets. Thus it can
be stated that business analyst is one of the most efficient process for managing the data sets
associated with the organization. Business analyst will be capable of providing the insight of the
business and the ways through which the business can be developed. With proper business
analyses it will become easy to meet the requirements of the customers. Business analyst is
important for managing the stakeholders and also focuses on gathering the documents and
analyses the need of the current business. With the help of proper business solution it will
become easy to provide a better technical support to words the business performance. However it
is important for business analyst to identify the major objective so that both the needs are
associated with the organization can be fulfilled. With proper analysis and effective control over
the data sets it will become easy to manage the data components. This will offer an efficient way
to manage the data components.

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Bibliography
Balachandran, B.M. and Prasad, S., 2017. Challenges and benefits of deploying big data
analytics in the cloud for business intelligence. Procedia Computer Science, 112, pp.1112-1122.
Bernard Marr. 2020. Amsterdam Fire Department: The Use Of Big Data Analytics In Fighting
Fires. [online] Available at: <https://www.bernardmarr.com/default.asp?contentID=1082>
Bernard Marr. 2020. Big Data And Art: Can Machine Learning Technology Recreate The Work
Of Gaudi?. [online] Available at: <https://www.bernardmarr.com/default.asp?contentID=715>
Elijah, O., Rahman, T.A., Orikumhi, I., Leow, C.Y. and Hindia, M.N., 2018. An overview of
Internet of Things (IoT) and data analytics in agriculture: Benefits and challenges. IEEE Internet
of Things Journal, 5(5), pp.3758-3773.
Erl, T., Khattak, W. and Buhler, P., 2016. Big data fundamentals: concepts, drivers &
techniques. Prentice Hall Press.
Maione, C. and Barbosa, R.M., 2019. Recent applications of multivariate data analysis methods
in the authentication of rice and the most analyzed parameters: A review. Critical reviews in food
science and nutrition, 59(12), pp.1868-1879.
McKinsey & Company. 2020. Analytics Translator: The New Must-Have Role. [online]
Available at: <https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/
analytics-translator>
skills, C. and careers, J., 2020. Data Visualisation Analyst: Job Description. [online]
TARGETjobs. Available at: <https://targetjobs.co.uk/careers-advice/job-descriptions/454283-
data-visualisation-analyst-job-description>

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University of Wisconsin Data Science Degree. 2020. What Do Data Scientists Do? | University
Of Wisconsin Data Science. [online] Available at: https://datasciencedegree.wisconsin.edu/data-
science/what-do-data-scientists-do/
Vassakis, K., Petrakis, E. and Kopanakis, I., 2018. Big data analytics: Applications, prospects
and challenges. In Mobile big data (pp. 3-20). Springer, Cham.
Villanovau.com. 2020. [online] Available at: <https://www.villanovau.com/resources/business-
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