Answer To: ITECH7406 Business Intelligence and Data Warehousing, SEM1, 2020 Assignment #2 (Team Presentation) &...
Payal answered on May 29 2021
BUSINESS INTELLIGENCE &
DATA WAREHOUSING
TABLE OF CONTENTS:
1. PURPOSE
2. INTRODUCTION TO BI TOOLS
2.1. SAP ANALYTICS CLOUD
2.2. TABLEAU
3. DOMAIN SELECTION
3.1 HEALTHCARE ANALYTICS
3.1.1 DATA ANALYSIS
3.2 MANUFACTURING
3.2.1 DATA ANALYSIS
4. ROLE OF BI TRENDS
4.1 MASTER DATA MANAGEMENT
4.2 DATA VISUALIZATION
5. IMPACT OF DATA ANALYTICS & BUSINESS INTELLIGENCE
5.1 IMPACT ON HEALTHCARE ANALYTICS
5.2 IMPACT ON MANUFACTURING
6. CONCLUSION
1.PURPOSE:
The basic objective of this activity is to develop an understanding on the importance of Business Intelligence & Data Warehousing in Organizations. The detail understanding on approaches followed by Organizations & practice followed thereafter in the real world to uncover the hidden challenges & helps in meeting Organizational objectives.
We shall be considering SAP Analytics Cloud & Tableau for our study
2.INTRODUCTION TO BI TOOLS:
2.1 SAP ANALYTICS CLOUD (SAC) -
SAP Analytics Cloud is part of SAP Cloud for planning product, which was released in 2015. Apart from business planning, the other key components are Business Intelligence (for reporting, dashboard analysis using Graphs & Maps, data-discovery and visualization), predictive analytics and governance, risk, and compliance.
SAP Analytics Cloud allows data analysts and business decision makers to visualize, plan and make predictions all from one secure, cloud-based environment. SAP claims this differs from other BI platforms, which often require data to be integrated from various sources and users to jump between different applications when performing tasks, such as creating reports.
SAP Analytics is being widely used in all domain area like Manufacturing, Banking, Telecommunication, Retail, IT, Infrastructure etc. Powerful Dashboards & Visualizations are being used by top management & board members of organization to analyse company performance & trends and thus helping in making decisions to forecast.
SAMPLE DASHBOARD:
TABLEAU:
Tableau is a powerful data visualization tool used in the Data Analytics and Business Intelligence Industry. It helps in simplifying raw data which in turn can be easily turned into an understandable format., to gain meaningful insights out of the data
The great thing about tableau is its user-friendliness it offers to the users for various analysis. By using Tableau, even a non-technical user can create a customized dashboard. The best feature Tableau are
· Data Blending
· Real time analysis
· Collaboration of data
Over the years the tool has attracted the attention of people from all sectors such as business, researchers, different industries, etc.
Moreover, to promote the product within educational institutions, students at college level, it offers a Tableau student version which is free for the students up to a period of one year. (Anoshin, 2019) (Baldwin, 2019.1)
SAMPLE DASHBOARD:
3. DOMAIN:
Let us understand the concept of Business Intelligence Tool & Data Warehousing in the real world. Here, we are considering 02 domains for our details study –
1) Healthcare Analytics – Business Expansion Analysis
2) Manufacturing – Financial & Operational Efficiency
3.1 HEALTHCARE ANALYTICS (Business Expansion Analysis):
Healthcare analytics involves collecting and analysing of data in the healthcare industry in order to gain insights for better decision-making. From key areas like Medical Facility, Emergency Facilities, Mortality Rate etc in healthcare analytics can be used on both macro and micro levels to effectively streamline existing business operations, new business expansions, improve patient care, and lower overall costs.
Healthcare analytics has grown immensely over the past few years. It has empowered the firms operating in the healthcare sectors to take better decisions that align with the business as well as the societal objectives. The use of data analytics helps in managing the beds at the hospital level for various disease and plan it according to the specific needs.
This data is about Medical Care Facilities within each city in various States. The major categorization is done bases on the type of facility (Government or Private). Further it also measures each Medical facility care centre by Mortality rates in comparison to national average, overall rating and availability of Emergency facilities within each Medical facility centre (Sabyasachi Dash, 2019) (Datasheet, 2020)
SAMPLE DATASET:
3.1.1 DATA ANALYSIS:
Here we are going to consider the data of Healthcare sector to build our analysis & visualization in TABLEAU in order to draw some meaningful insights, so that we can add value to our business. (Tableau has been recognized as one of the Top Analytical tool by Gartner Survey over the years) (Ritesh Chugh, 2013)
3.1.1.1 Scope -
The scope of the analysis in this particular sheet is to analyse the count of Medical facility centres within each city.
Conclusion -
It can be seen from the above analysis that most of the city are having count of Medical facility ranging from 1 to 5 while in other few, Medical facilities are ranging from 6 to 33.
Recommendation -
It seems a wise decision to invest in the cities having only 1 to 2 facility centre, due to less competition as well as to serve the people who have been side-lined due to their locational constraint. (Murray, 2013)
3.1.1.2 Scope –
To analyse the distribution counts of Medical facility within each County in respective Cities
Above image is a sample image of analysis output. Refer Tableau output in pdf for full visibility of graph
Conclusion -
It is observed that though the City might contain multiple number of Medical facilities but these are spread over different Counties.
Recommendation -
It is advisable to consider the Counties having only 1 Medical facility centre in the current situation. The sorted is to be be further analysed based upon other parameters taking into account. (e.g Patient experience, Special facilities, etc) (Winter, Sep,10, 2015)
3.1.1.3 Scope –
To analyse the Counties having Single Medical facility centre on the basis of Overall Rating and Patient experience.
Segregation is done on the basis of overall rating 1- Very Bad and 5 -Best. Further to add our analysis we add patient experience of the respective facility centres.
Conclusion –
It can be seen that Orange colour refers to Patient Experience below the national average. Here the overall rating is either 1 or 2. So, it can be concluded that overall rating of a facility centre depends on Overall patient experience.
Recommendation -
It is advisable to consider Overall rating of a facility centre, while deciding the location factor, as it tell about the Patient satisfaction level. (Anoshin, 2019)
3.1.1.4 Scope –
Moving further with our analysis we filter the Medical facility centre having overall rating 1 and Patient experience in Orange colour i.e.- Below the National average patient experience. This filtered out data is further analysed based upon availability of Emergency services (Yes/No) & type of Hospital ownership (Government/ Private/ Voluntary).
Conclusion -
As we can see that each facility centre is coloured according to the Hospital ownership type. To drill down further to our analysis, we also add the availability of Emergency service within each facility centre with Yes or No. It can be seen that either the Government at local level or Voluntary non profit do not have any Emergency Facility available with them. There are total 4 such Counties.
Recommendation -
So we have filtered out the rest of the counties from our analysis and should focus on these 4 particular counties to set up new Business operations, where there is a high scope & need for Emergency services.
3.1.1.5 Scope –
Here, Relationship between overall rating of a facility centre and Mortality rate comparison in that particular facility centre.
Conclusion -
It can be seen that even the facility centres having higher mortality rate than the national average have overall rating of 5 or 4.
So, it can be concluded that overall rating of a Medical facility centre does not depend on the mortality rate of respective facility.
Recommendation -
As Overall rating does not depend on Mortality rate, therefore Mortality rate can be ignored while deciding the locational factors, as high Mortality could be due to other factors.
3.1.1.6 Scope –
In this particular analysis we will be analysing how the Patient experience varies across the Hospital type.
Conclusion -
It can be seen that due to non-disclosure of data, we can analyse Patient experience only for the Acute care and Critical Access Hospitals. It can be seen from the above analysis that Patient experience for the Acute care Hospitals is not satisfactory, where almost 32%...