Mortality Caused by Road Traffic PDF

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Mortality Caused by Road Traffic
Student Name
Institutional Affiliation

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Executive Summary
The concept of data visualization has evolved over the years from the traditional Microsoft excel
spreadsheets to more advanced visual representations such as dials and gauges, fever, pie, and
bar charts that are more detailed, infographics, heat maps, spark lines, and geographic maps.
Data analytics software like tableau allow users to manipulate and interact with the data through
querying and examination. The project will be focused on mortality that has been cause by road
traffic accident. The analysis will be done on tableau to come up with a clear picture of this
phenomenon. Road traffic accidents is one of the leading cause of deaths across the world and
make up a high percentage of ill-health burden such as paralysis. From the data we found out that
the number of road accidents was much higher in developing countries as compared to developed
countries. This has been attributed to insufficient traffic infrastructure in such countries.
Additionally, accidents were more in urban areas as compared to rural areas. Data Visualization
enables the users to configure the software to automatically generate dashboards that can be used
to track traffic accidents across the globe and represent them visually. Many countries are now
implementing data visualization tools to monitor several government initiatives including traffic
incidences.

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Table of Contents
Executive Summary.....................................................................................................................................2
Introduction.................................................................................................................................................4
Project overview..........................................................................................................................................4
Data Source.................................................................................................................................................5
Member's Contribution................................................................................................................................5
Project Execution........................................................................................................................................5
Visuals and Screenshots..............................................................................................................................5
Technical Approach.....................................................................................................................................8
Results.........................................................................................................................................................8
Self-reflection..............................................................................................................................................8
Conclusion...................................................................................................................................................9
Bibliography..............................................................................................................................................10

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Introduction
Data visualization is a very important concept in data analysis and interpretation and is very
significant in representing the data visually using graphs, charts and other visual patterns.
Trends, patterns, and relationship that may not be identified by just looking at the data can be
easily recognized through data visualization. The concept of data visualization has evolved over
the years from the traditional Microsoft excel spreadsheets to more advanced visual
representations such as dials and gauges, fever, pie, and bar charts that are more detailed,
infographics, heat maps, spark lines, and geographic maps. Data analytics software like tableau
allow users to manipulate and interact with the data through querying and examination. It also
notifies the users for any change in the data set. Data visualization has grown to be a de facto
basis for business intelligence. Tableau- which is one of the business intelligence tool, has
enabled organizations and institutions to analyze big data by emphasizing on visual approach.
The project being undertaken will utilize tableau software to analyze and interpret mortality that
has been cause by traffic accidents across the globe. The data available for analysis is vast and
thus cannot be interpreted by just looking at it or using the traditional methods because it will
take a longer time. This is the reason why tableau was chosen to help in representing the data
visually through graphs and infographics. Data visualization is very essential in this project in
will help in making data-driven insights and democratizing analytics and data available to the
transport institutions and organizations. Therefore, Tableau will play a vital role in the analysis
of the data.
Project overview
The project will be focused on mortality that has been cause by road traffic accident. The
analysis will be done on tableau to come up with a clear picture of this phenomenon. Road traffic
accidents is one of the leading cause of deaths across the world and make up a high percentage of
ill-health burden such as paralysis. Every year, it is estimated that more than 1.2 million people
die duce to road carnage and another 50 million injured. The world health organization (WHO)
has predicted that is proper measures are not put into place then, then road accidents by 2020 will
be the third-leading cause of burden injury, disease, and deaths. The developing countries are
facing a major burden making more that 80% of the annual deaths caused by traffic accidents.

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Data Source
The data was extracted form world bank https://data.worldbank.org/indicator/SH.STA.TRAF.P5
which is data that was retrieved from WHO Global Status Report on Road Safety. The data gives
a record of mortality that has been brought about by road traffic fatal injury deaths per 100000
populations1.
Member's Contribution
Every member was task with one activity to analyze the data in various categories such as the
time when accidents occurred, where the accidents occurred, accidents in urban and rural areas,
purpose of the journey, and type of vehicle.
Project Execution
In order to load this project, first install the tableau. There are two option which you can run the
project; you can either double click on the project and choose to open with tableau or open
tableau, go to File> import workbook select the file and click on open.
Visuals and Screenshots
Figure 1: Road Accident Sites
1 Worlbank Worldbank, "Mortality Caused by Road Traffic Injury (per 100,000 People)," Mortality Caused by Road
Traffic Injury (per 100,000 People) | Data, , accessed November 03, 2018,
https://data.worldbank.org/indicator/SH.STA.TRAF.P5.

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Figure 2: Accident Timeline
Figure 3: Road Accidents

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Figure 4: Car Passengers
Figure 5: Accidents in Urban Vs Rural Areas

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Figure 6: Accident Details
Technical Approach
We loaded the data to the tableau so that we can get a visual representation of the data. Tableau
is such a great tool to analyze big data so as to get deeper insights about the data and generate
usable knowledge that can be applied in solving problems.
Results
From the data we found out that the number of road accidents was much higher in developing
countries as compared to developed countries. This has been attributed to insufficient traffic
infrastructure in such countries. Additionally, accidents were more in urban areas as compared to
rural areas.
Self-reflection
While carrying out this project I realized that the number of accidents have reduced over the
years in the developed countries. This has been attributed to successful inventions such as speed
limits, safety belts, banning drinking while driving, better and safer road designs and vehicles. It
was a nice experience to be able to analyze big data and be able to come up with useful
information that can be interpreted to better understand the phenomenon under study. Tableau is

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such an effective tool in big data analysis because it gives various options to analyze and
compare the different aspect of data. It is a data visualization software that has the capability to
support data blending, complex computations, and dashboard creation to come up with
interpretable and meaningful data visualizations that give more knowledge which cannot be
noted or identified by just looking at the spreadsheet. Some of the benefits that I realized when
interacting with tableaus is that it offers a quicker way to come up with interactive visualization,
easy to implement and use, has the capacity to handle large volume of data, other scripting
languages such as R and Python can be incorporated into Tableau, facilitates creation of
responsive dashboards, and mobile support2. However, the software does not provide report
notification and scheduling, lack custom visual import, single and static value parameters,
limited formatting, limited data processing and low resolution in tableau dashboards.
Conclusion
Data visualization software such as tableau have several uses including being used as a business
intelligence reporting tool. It enables the users to configure the software to automatically
generate dashboards that can be used to track traffic accidents across the globe and represent
them visually. Many countries are now implementing data visualization tools to monitor several
government initiatives including traffic incidences. The software further helps data scientist and
engineers to monitor their sources of data and carry out basic data analysis before or after in-
depth and advanced analysis of data.
2 Dong Hwan Kim, "A Case Study of Producing Infographics Using Tableau Public," Journal of Korea Spatial
Information Society 23, no. 2 (2015): , doi:10.12672/ksis.2015.23.2.021.

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Bibliography
Kim, Dong Hwan. "A Case Study of Producing Infographics Using Tableau Public." Journal of
Korea Spatial Information Society23, no. 2 (2015): 21-29. doi:10.12672/ksis.2015.23.2.021.
Worldbank, Worlbank. "Mortality Caused by Road Traffic Injury (per 100,000 People)." Mortality
Caused by Road Traffic Injury (per 100,000 People) | Data. Accessed November 03, 2018.
https://data.worldbank.org/indicator/SH.STA.TRAF.P5.