Bird Strike Analysis Using SAS Visual Analytics

Student Name Student ID
Big data Analysis Using SAS Visual Analytics
ITECH1103- Big Data and Analytics Group Assignment – Semester 1, 2019

Table of Contents
Executive Summary.....................................................................................................................................2
Background..................................................................................................................................................2
Dashboard...................................................................................................................................................4
Additional Visualizations.............................................................................................................................6
Findings of the Analysis.............................................................................................................................10
Discussion of the Findings.........................................................................................................................19
Reflection..................................................................................................................................................20
Conclusion.................................................................................................................................................21
References.................................................................................................................................................21
Appendices................................................................................................................................................23
Additional visualizations........................................................................................................................23
Analysis..................................................................................................................................................26
Dashboard.............................................................................................................................................32

Executive Summary
The report discusses the overview of bird strike dataset analysis findings. In this project,
BIRDSTRIKE_DATA set is used for the analysis. SAS visual analytics platforms are used in this
project. Mostly tables and bar charts are used in this project to show the findings of the
conducted analysis. From the conducted analysis different facts related to the bird strikes and
its impacts on the airline services are founded. Bird strikes are the major problem to the aircraft
operators. Mostly all the major aircraft operators affected by the bird strikes. Nearly 348
species are the major reason for the bird strike. Southwest airlines involved in most of the bird
strikes. Most of the bird strikes occurred during the approaching phase. Also, suggestions for
mitigating the bird strike are given in this report.
Background
Bird strike is one of the major problem faced by various aircraft operators all around the
world. Throughout the world, bird strike is one of the important reason for the losses and
accidents of the aircraft. In general, it is caused by birds as well as some ground animals. The
chosen data set contains the pieces of information about the various bird strikes. Here the
dataset contains the information of the bird strike from 2001 to 2011. The dataset contains
information about the various wildlife species mostly affected by the bird strike. From the
chosen dataset we also know about the various aircraft operator who faced bird strikes on the
selected time frame. All these details are analyzed using the SAS visual analytics software. This
software allows the users to carry out the visual analysis of the dataset (Blascheck, John,
Kurzhals, Koch & Ertl, 2016). By using this software we can develop different visual reports.
These visual reports help to improve the understanding of the results founded from the
analysis.
SAS Visual Analytics:

SAS Visual Analytics is a web-based product that has an increased performance on the analytics
technologies. It discovers the large data of an organization to identify the patterns, chances and latest
trends. The combination of data, outline of data and empower the predictive analysis of data. The
exploration of data and mining are made in an easier way. The SAS LASR Analytics server combines
with the SAS Visual Analytics Explorer of interface for drag and drop of data and for the high visual
content. This makes an organization to value the enormous amount of data. This results in easier
problem solving, to improve the performance of the business, for future prediction and to face risk. The
SAS Visual Analytics Designer is used to create the reports and dashboard for the particular devices and
webs. The models that are created, tested are based on the patterns used for finding the information
about the data.
Overview of visualizations
The SAS Visual Analytics Explorer exhibit the data by using the visualizations.
Visualization Types
 Automatic chart
Selects the type of chart in automatically which is on the data and that sets the
visualization. At first, that survey a new set of data. That gives a chart view of the data.
 Table
It displays the data in the table. It is used to test the data source and that should
rearrange the data columns and sort.
Benefits of using SAS Visual Analytics
In SAS Visual Analytics, the user is to increase the analytic power in the data and to
search the fresh data sources, investigate the team and to design uncover which belongs to the
patterns. Then it is very comfortable for the visual in reports. The traditional reporting is to be

prescribed that requirement of the search and to send. When the generalized data are
succeeded then we have to include the reports are added into the mobile device or in the SAS
Visual Analytics Viewer.
It provides the users from the following benefits:
 It allows the user to add the power, it shows the huge amount of data.
 It authorizes the user to search the data and different measures with heavy speeds.
 It allows the users to allocate awareness everywhere via the web/mobile device.
Dashboard
Reasons for Using Movement
Playable dashboards are very easy to create and it is useful. But we have to review for a
short time. If you want to set your report in motion, why?
Where the link of the kiosk (small enclosed structure with the open on one side) and
Booth (small stall for the display, sale of goods to sell newspapers, cigarettes) for a short
duration.
At presentation, we have to determine how long does each page displays and explain
about the keys and displays report of the distraction of each page.
Design considerations for playable dashboards
The aim of the report moves on to the kiosk or a booth, we have to need the
information to move faster. The key and diagrams are held quickly except the playable
dashboards.
A multiplex report is to be reported by the use of small font and the multiple different
objects, then the audience is occupied from the report (Bodén & Stenliden, 2019).

The report object is necessary to need your first look and then the entries of the data
(graph) are set to move at a fast rate in per page with three or four seconds.
Example of a playable Dashboard
The report created describes the bird strikes by the aircraft. The report has 25,558 rows
of data. The bar chart is used to compare the data and geomap to report the object. The
geomap has icons, buttons, colors and it is associated with that legend of the display in the
graph. The values are displayed on the color scale in the graph.
The report has a geomap, statistics and a bar diagram. The geomap represents the
frequency of bird hit on the particular continent of the area. The frequency ranges from 2520 to
less than 820. The Asian continent has high frequency and the South American continent is low
at frequency. The statistical report is about the total cost collected for remains of wildlife. Sun
River airport has spent the total cost of 10 million. The bar diagram represents the frequency

condition of precipitation during various climate change. The frequency of precipitation is
higher in the season other than fog, rain, and snow. And there is no precipitation on rainy and
snowy seasons ("Editorial Note: Advances in Visual Analytics and Mining Visual Data", 2018).
Justifications for the used visual elements on this project
In this analysis, we used bar charts and cross tables for visualizing the findings. We used
bar charts and pie charts because they are very easy to understand. The bar chart shows the
relationship between the variables very clearly. By using that we can compare the different
variables. Also, cross tabulation also a quite simple method for understanding. It doesn't
requires huge statistical knowledge to interpret.
Additional Visualizations
In this section of the report the evidence of some other deep investigations are given.
Here the six different aspects on the given dataset are analyzed.
Relation between Aircraft size and bird strike frequency

There is a significant relationship between the aircraft size as well as bird strike
frequency. From the given graph that is clear in the total bird strikes nearly half of them happen
to the large aircraft. But at the same time, we need to consider another thing. In large aircraft,
most of the bird strikes are a single or small group. The graph shows clear evidence. Here a
large number of bird groups not struck on the large aircraft.
Impact of bird size and Aircraft size on the bird strike
The above-given cross table shows the relation between the bird size and aircraft size
and bird strike frequency. In total bird strikes, most of the bird strikes are caused by the