Enterprise Planning and Implementations: Big Data Feasibility Report

This report assesses the feasibility of implementing big data analytics within the Ramsay Healthcare center. It begins by identifying project stakeholders and then details the information and technology architectures essential for big data systems. The report outlines governance methodologies, work breakdown structures, and critical success factors for the implementation. It further examines the anticipated impact on the organization, including improved operational efficiency, enhanced patient care, and cost reductions. The study also explores the use of predictive models, data quality control, and economic burden estimation. Finally, the report offers recommendations, emphasizing the importance of data accessibility, quality, and leveraging big data for profit, ultimately concluding with a comprehensive overview of the benefits and challenges of big data adoption in healthcare management. The report highlights the importance of data governance, stakeholder engagement, and the application of big data analytics to achieve business goals, improve customer experience, and drive bottom-line growth within the healthcare sector.

Running head: ENTERPRISE PLANNING AND IMPLEMENTATIONS
Feasibility of Big Data in Healthcare Management
Name of Student-
Name of University-
Author’s Note-

1ENTERPRISE PLANNING AND IMPLEMENTATIONS
Table of Contents
Project stakeholders for Big Data Analytics Systems.....................................................................1
Information architecture for big data analytics systems..................................................................1
Technology architecture for big data analytics systems..................................................................3
Governance and methodologies used for the system.......................................................................5
Work breakdown and work package decomposition.......................................................................6
Critical success factors for the system.............................................................................................7
Impact of implementation on organization......................................................................................8
Recommendation and conclusion....................................................................................................9
References......................................................................................................................................11

2ENTERPRISE PLANNING AND IMPLEMENTATIONS
Project stakeholders for Big Data Analytics Systems
The customers in Ramsay Healthcare center will get improved operational efficiency
compared to previous service that were provided by the company. The customer will be able to
get medical claims and will be able to get mobile data and can get service from non-retail outlets.
With big data customers will be able to get pharmacy claims from the pharmacists who is a
stakeholder for the healthcare center (Mehta and Pandit 2018). The customers will have to
communicate with the customer care representatives who will help the customers in case of any
issues. The patients will also receive advanced treatment process from the doctors and medical
professionals with the help of big data analytics implementation in Ramsay Healthcare center.
Information architecture for big data analytics systems
Information architecture is known as enabler in system of big data analytics. Big data
includes different data that are structured. Semi-structured and unstructured. The main
characteristics of big data that can be included in Ramsey Health care centers includes volume,
variety and velocity and implementing those characteristics in the health care center is quite a
challenging work in the existing architecture of the hospital.
To obtain the maximum value from the big data, the hospital needs to handle the fast
delivery rate and has to handle the large amount of data having different data types. The different
types of data from the organization can be integrated with the enterprise data and can be
analyzed simultaneously (Wang, Kung and Byrd 2018). The information architecture that is used
in Ramsey health care center includes tool as well as methods that helps in organizing
relationships, building as well as labeling relationships in the organization. Information
architecture involvement helps big data to explore as well as analyze different types of data

3ENTERPRISE PLANNING AND IMPLEMENTATIONS
sources. Information architecture is needed to exploit relationships and also helps to synergies
the data in the organization. The big data components that are used in the health care center
along with the information architecture element are provided below in the table.
Information
Architecture
Element
Volume Velocity Variety
Content Quality of
Service
This mainly focuses
on the availability,
usefulness, security
and the scalability of
data content and also
improves the quality
of the content.
Helps to eliminate all
the delays as well as
latencies from
content as well as
from the business
processes. This
results in analyzing
and making proper
decisions that affects
the velocity of the
content.
Helps in improving
quality of different
content that are
included in Ramsey
Health care.
Content Governance Mainly focuses on
the accountability
establishment
specifically for
accuracy, timeliness
as well as
This helps to improve
the velocity of the big
data by making
smaller pertinent
content from the
large amount of data
The resources
included in big data is
trimmed by content
governance.

4ENTERPRISE PLANNING AND IMPLEMENTATIONS
consistency. (Manogaran et al.
2017).
Content Access This helps in
searching as well as
establishing all
standard types for the
searches that are
made. Content access
will include large
volume of data by
establishing
parameters on each
search (Wang and
Hajli 2017).
Has the ability for
accessing content and
helps to speed along
with efficiency where
content can be
accessed.
Shows how content
variety can be
accessed. This will
often drive all search
parameters that are
used for accessing
different content.
Content organization Will provide business
rules for identifying
relationship between
the content in the
organization.
Improves speed for
accessing the content
and this is done by
applying the meta
data.
This drives
relationships as well
as includes different
content types in the
organization.
Technology architecture for big data analytics systems
BI in Ramsey health care is classified in to three categories, first is categorized by content
that are DBMS based and are structured content. This helps to utilize the analytical tool that is

5ENTERPRISE PLANNING AND IMPLEMENTATIONS
traditional through data warehousing as well as through data mining (Kankanhalli et al. 2016).
Second includes content that is web based and unstructured content. This helps to utilize the
tools in the information retrieval. Web analytics, opinion mining, and analysis of network and
also can helps in social media analytics. Third includes content that are mobile based and sensor
based. This helps to utilize the tools in analysis of local awareness, in person centered as well as
includes mobile visualization.
The architecture of big data analytics is shown in figure 1 and the architecture is capable
of utilizing the frameworks parallel, processing as well as distributed storage and the frameworks
are basically provided by Hadoop as well as by MapReduce. In Big data, there is data
warehousing which is considered to be the viable technology store large number of data (Galetsi
and Katsaliaki 2019). There is also a connection between the Hadoop as well as in data
warehousing. There are unstructured data from the sensors, from social media as well as from
web applications that are usually stored in Hadoop.

6ENTERPRISE PLANNING AND IMPLEMENTATIONS
Figure 1: Technical architecture of Big Data Analytics
(Source: Ristevski and Chen 2018)
Governance and methodologies used for the system
Data governance that is used in the organization enables the organization in realizing the
standardization of the systematic data as well as includes integrated management. Managing the
application system systematically helps in establishing the organizations as well as processes, the
policy information as well as includes establishment for the business processes. For establishing
proper data governance, there should be a connection with corporate governance, the information
technology architecture and the IT governance from the perspective of the company (Ta, Liu and
Nkabinde 2016). Governance that is included in the Ramsey health care includes set of
processes, policies laws, institutions as well as customers that are administered as well as

7ENTERPRISE PLANNING AND IMPLEMENTATIONS
controlled. The organization is to develop a team for defining their data quality so that they can
perceive data asset for their organization.
The methodology that is included while implementing the big data analytics is differ
from traditional statistical approach for the experimental design (Krishnan 2016). The analytics
of big data includes approach for predicting the response behavior or helps to understand how
the data can be retrieved. This helps in generating the statistical model in which assumptions
such as independence, randomization as well as normality are included.
There is no particular unique methodology that can be used for implementing big data.
After defining the problem in the organization, research should be conducted that would help to
design the methodology that should be used for rectifying the problem in the organization. But
there are certain guidelines that are relevant for solving the problem of the organization.
One modelling that can be used in big data analytics is statistical modelling. This
includes supervised classification as well as all the regression problems that are included in the
organization processes.
Work breakdown and work package decomposition
The work package that is to be carried out for implementing big data analytic sin Ramsey
health care are:
1. Developing proper data analysis plan as well as includes standard operating procedure
for the research objective for ensuring transparency as well as include effective communication
for the stakeholders involved (Shafqat et al. 2018).

8ENTERPRISE PLANNING AND IMPLEMENTATIONS
2. Carrying out project data exploration, visualization as well as includes basic statistics
that covers insights in research question that are addressed in the research.
3. Implementing measure for data quality control for ensuring data errors as well as
including outliners that are controlled and identified ensuring reliable data that are possible.
4. Developing predictive models that would provide outcomes, the disease progression as
well as will include therapy selection that are actually based on the advance analytics (Suneetha
2019). This would include to carry out an investigation that would add value to the clinical as
well as to the biological biomarkers so that predictions can be improved.
5. Assessing performance for predictive models for existing methods and developing
patient scoring as well as evaluation process.
6. Using a database that would help in estimating economic burden for the disease that
also depends on the region where the patient lives. The outputs that will be generated will inform
the policy issues, and will also provide all the inputs that are needed.
Critical success factors for the system
The results that comes from the system of big data analytics are to be applied in the
existing system for improving the present workflow and well as increasing the awareness and
should be used for securing the bottom line (Shahbaz et al. 2019). The system of big data
analytics also results in having positive customer experience with the service that is delivered by
the organization. There are five critical factors that are used for successful implementation of big
data analytics. The five critical factors are:

9ENTERPRISE PLANNING AND IMPLEMENTATIONS
1. Clearing the business goals for the company that aims in achieving in the project of
implementing big data analytics (Alotaibi, Mehmood and Katib 2019).
2. The data sources that will be used in the project should be relevant with the project so
that there is no duplicates or have unimportant results included in the project.
3. There should be completeness for the data for ensuring the essential information that is
to be covered.
4. There should be result for application of big data analysis for meeting the goals that
specific for the project.
5. There should be engagement of the customer and there should be a bottom line growth
as indicators for success data mining in the project.
Impact of implementation on organization
Big data analysts can be benefitted in the organization if the data that are accrued are
analyzed properly instead of storing or collecting (Wang et al. 2018). The main benefits that is
used for business is it helps in proper decision making that results in increasing the productivity
of the organization. Big data implementation in healthcare sector will help the company to
improve its quality as well as will help to cut down their maintaining cost.
The big data analytics would help in right living as because the data that are collected
will help the patients to take role in their own diet, exercise, as well as they will be interested in
medication adherence so that they can control their health (Johri et al. 2017). The data that the
patients would get from big data would help to improve their outcomes which would help to
reduce the medical errors. Implementation of big data analytics in Ramsay Health care would

10ENTERPRISE PLANNING AND IMPLEMENTATIONS
also facilitate care that is evidence based and is personalized to some specific patient (Ramesh,
Suraj and Saini 2016). The outcomes that comes from big data analytics provides the best
medical data that helps in better provider skill. Big data analytics also includes cost effective
method in the process of healthcare that provides reimbursement as well as includes eliminating
fraud, abuse as well as waste in the utilization of big data.
Ramsay health care center will be able to analyze the history data of patients, can also
monitor the real time data from the monitors, includes clinical factors, and also can monitor the
lifestyle choices from the implementation of big data.
Recommendation and conclusion
1. Accessing, availability and quality of big data: It is recommended to implement more
appropriate processes to leverage the data along with privacy as well as with ethical principles so
that they can be accessed easily.
2. Profit from big data: There should be proper approaches that are to be developed by
Ramsay health care center that would allow cooperation of humans and machines for exploiting
the big data for having better health. This would help to improve the interactivity and improve
the trustworthiness for the project.
3. Data analytics including multi modal: There is a need for technology that will be able
to handle, exploit as well as analyze the data that are complex in the organization.
4. Healthcare knowledge: The wearable sensors that are used by the patients and users are
to be known. Proper knowledge regarding the healthcare wearable are to be known to the users
so that they can use the application properly. There are many new approaches that brings big

11ENTERPRISE PLANNING AND IMPLEMENTATIONS
data as well as knowledge together. Knowledge in big data should have better data sense and
data can be used for generating better knowledge.
5. Ethics and privacy in big data: More approaches are to be applied for balancing benefit
as well as threats that are more detailed and are more sensitive for the data that are being
available.