Deliverable 7

ISM6200CBE Section 01CBE Business Intelligence and Analytics (11 Weeks) – CBE OnlineCourse – 2024 Spring Quarter
Deliverable 7 – Emergency Call Data Analysis
Deliverable 7 – Emergency Call Data Analysis
Assignment Content
1.
Competency
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Evaluate business intelligence (BI) frameworks.
Compile data required to inform business insights.
Conduct comparative market and operational performance analyses.
Determine business outcomes using predictive analysis techniques.
Analyze big data for business decision-making.
Identify emerging technologies that impact analytics, business intelligence
(BI), and decision support.
Student Success Criteria
View the grading rubric for this deliverable by selecting the “This item is graded
with a rubric” link, which is located in the Details & Information pane.
Scenario
You have recently been hired as an Emergency Services Analyst for the city of
Lincolnton, NC. In this role, you are to analyze all emergency services incident
patterns, collect statistics, prepare and disseminate information, and assist with
special projects. Recently, you have been tasked with conducting analysis on the
emergency services data from 911 related calls from around the city.
Part 1: You receive the email from your Director of Emergency Services, including
an Excel file of source data, and are asked to analyze the calls from around the
community. You will perform your analysis (in the same Excel spreadsheet) and
provide an explanation in an email response (Word document). Download the
source data file below.
Emergency Call Center Data File
Within the spreadsheet, perform the following:
A. Prepare a dataset from the “Source Data” spreadsheet. Remove any potential
errors or outliers, duplicate records, or data that are not necessary. Provide a clean
copy of the data in your email response. Copy and paste the Source Date in your
Excel Spreadsheet and label the sheet, “Source Data”. Copy and paste the Clean Data
Sheet in your Excel Spreadsheet and label it, “Clean Data Sheet”.
B. Explain why you removed each column and row from the “Source Data”
spreadsheet or why you imputed data in empty fields as you prepared the data for
analysis.
C. Create data sheets using your cleaned dataset and provide each of the following to
represent the requested aggregated data.
a. Table: date and number of events OR
b. Bar graph: date and number of events
c. Label this table or bar graph in your Excel Spreadsheet, “Data and Events”
a. Table: number of incident occurrences by event type OR
b. Bar graph: number of incident occurrences by event type
c. Label this table or bar graph in your Excel Spreadsheet, “Event Type”
a. Table: sectors and number of events OR
b. Bar graph: sectors and number of events
c. Label this table or bar graph in your Excel Spreadsheet, “Number of Events”
D. Summarize your observations from reviewing the datasheets you have created
and include it as part of your introduction to your analysis report analysis in Part
2. Copy and paste your Excel spreadsheets in your Part II Word document (Analysis
Report) and write your observations on each chart.
Part 2: Further, the state has offered an additional funding incentive for police
departments that are able to meet the standard of having a minimum of 2.5 officers
onsite per incident. The Director has delegated the task to you to analyze the police
department’s data to determine if the department will be eligible for additional
funding. You will use the same source data provided in the Excel spreadsheet. In a
Word document, complete the following questions and include the summary from
Part 1 in an analysis report.
E. Create a table that shows the average number of officers assigned to each
sector. Also show the total number of incidents and total number of officers and
compute the overall average. Put this table in your Excel Spreadsheet and label it
“Avg Officers”. Copy and paste the table you created in your Analysis Report and
incorporate your comments on it.
F. Describe the fit of the linear regression line to the data, providing graphical
representations or tables as evidence to support your description. Display your
linear regression line in your Excel Spreadsheet and label it “Linear
Regression”. Copy and paste the graph you created in your Analysis report and
incorporate your comments on it.
G. Describe the impact of the outliers on the regression model, providing graphical
representations or tables as evidence to support your description. This should show
on your “Linear Regression” Excel Spreadsheet. Copy and paste the graph you
created in your Analysis report and incorporate your comments on it.
H. Create a residual plot and explain how to improve the linear regression model
based on your interpretation of the plot. Create the Residual Plot and display it in
your Excel Spreadsheet. Label the sheet, “Residual Plot”. Copy and paste the graph
you created in your Analysis report and incorporate your comments on it.
I. Conduct a comparative matrix for the sectors. Explain how your findings impact
the operations of the police department. Create your comparative matrix in your
Excel spreadsheet and label the sheet as “Comparative Matrix”. Copy and paste the
table you created in your Analysis report and incorporate your comments on it.
J. Describe the precautions or behaviors that should be exercised when working
with and communicating about the sensitive data in this scenario.
K. Discuss any additional tools or technologies that could impact the data collection,
storage, or analysis for future projects.
L. Provide attribution for credible sources needed in completing your report.
Instructions
Submit your email document, analysis report, and completed Excel file in one zipped
(compressed) file. For assistance with creating a zipped (compressed) file, please
visit the Rasmussen FAQ on How to Zip
Files: https://rasmussen.libanswers.com/faq/32413.
Resources
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Rasmussen College Writing
Guide: https://guides.rasmussen.edu/writing/professional
Grammar Checking – How do I create a Grammarly
account? http://rasmussen.libanswers.com/faq/32707
Discovery: https://guides.rasmussen.edu/discovery
ProQuest (PQ Central): https://guides.rasmussen.edu/pqcentral
APA Guide: https://guides.rasmussen.edu/apa
Submission
District Sector No. of Incidents Officers at Scene Event Type – V Event Type – NV Dates in June No. of Events in Sector H
B
83
158
45
38
1-Jun
3
H
125
165
61
64
2-Jun
4
W
37
86
23
24
3-Jun
2
K
64
131
38
26
4-Jun
5
D
60
121
39
21
5-Jun
6
O
31
72
15
16
6-Jun
4
U
52
96
25
27
7-Jun
6
R
60
124
36
24
8-Jun
4
S
44
82
16
28
9-Jun
3
1
1
27
14
10-Jun
4
J
41
77
28
34
11-Jun
3
Q
62
120
17
21
12-Jun
1
L
38
72
23
21
13-Jun
4
C
44
76
45
46
14-Jun
5
M
91
176
30
23
15-Jun
4
N
53
117
14
21
16-Jun
7
F
35
68
24
15
17-Jun
2
G
39
76
42
44
18-Jun
3
E
86
158
19-Jun
4
20-Jun
1
21-Jun
4
22-Jun
5
23-Jun
5
24-Jun
7
25-Jun
5
26-Jun
3
27-Jun
2
28-Jun
4
29-Jun
4
30-Jun
6
Deliverable 7 – Emergency Call Data Analysis
Rubric Details
Maximum Score
4 points
•
Grade for Deliverable 7
100% of total grade
A – 4 – Mastery
4
B – 3 – Proficiency
3
C – 2 – Competence
2
F – 1 – No Pass
1
I – 0 – Not Submitted
0
•
Criterion 1
0% of total grade
A – 4 – Mastery
Part 1: Prepared a cleaned dataset; provided a thorough and detailed explanation of changes to
source data. Datasheets were created that represent all of the requested aggregated data; no
errors present.
0
B – 3 – Proficiency
Part 1: Prepared a cleaned dataset; provided a clear and effective explanation of changes to
source data. Datasheets were created that represent all of the requested aggregated data but
contained some errors.
0
C – 2 – Competence
Part 1: Prepared a cleaned dataset; provided a reasonable explanation of changes to source data.
Datasheets were created that represent most of the requested aggregated data and contained
some errors.
0
F – 1 – No Pass
Part 1: Prepared a partially cleaned dataset; or provided an unclear or limited explanation of
changes to source data. Datasheets were missing for several of the requested aggregated data, or
datasheets contained many errors.
0
I – 0 – Not Submitted
Not Submitted
0
•
Criterion 2
0% of total grade
A – 4 – Mastery
Clearly and strongly conducted comparative market and operational performance analyses,
using clear examples in a well-crafted report. Comprehensive summary of observations of
datasheets; summary included as the introduction to analysis report.
0
B – 3 – Proficiency
Conducted comparative market and operational performance analyses, using some examples.
Strong summary of observations of datasheets; summary included as the introduction to
analysis report.
0
C – 2 – Competence
Conducted comparative market and operational performance analyses; no examples provided.
Adequate summary of observations of datasheets; summary included as the introduction to
analysis report.
0
F – 1 – No Pass
Unclear verbiage used when conducting comparative market and operational performance
analyses. Limited summary of observations of datasheets; or summary not included as the
introduction to analysis report.
0
I – 0 – Not Submitted
Not Submitted
0
•
Criterion 3
0% of total grade
A – 4 – Mastery
Part 2: Analysis report thoroughly describes the fit of the linear regression line to the data;
advanced graphical representations support the description. Thorough description of the impact
of the outliers on the regression model; advanced graphical representations support the
description.
0
B – 3 – Proficiency
Part 2: Analysis report clearly describes the fit of the linear regression line to the data; effective
graphical representations support the description. Strong description of the impact of the
outliers on the regression model; effective graphical representations support the description.
0
C – 2 – Competence
Part 2: Analysis report adequately describes the fit of the linear regression line to the data; basic
graphical representations support the description. Adequate description of the impact of the
outliers on the regression model; basic graphical representations support the description.
0
F – 1 – No Pass
Part 2: Analysis report minimally describes or does not describe the fit of the linear regression
line to the data; unclear graphical representations support the description. Limited description
of the impact of the outliers on the regression model; unclear graphical representations support
the description.
0
I – 0 – Not Submitted
Not Submitted
0
•
Criterion 4
0% of total grade
A – 4 – Mastery
Adequate residual plot created; advanced explanation of how to improve the linear regression
model based on interpretation of the plot. Advanced explanation of department qualification for
additional state funding, includes limitations, clearly based on linear regression analysis.
0
B – 3 – Proficiency
Adequate residual plot created; strong explanation of how to improve the linear regression
model based on interpretation of the plot. Strong explanation of department qualification for
additional state funding, includes limitations, clearly based on linear regression analysis.
0
C – 2 – Competence
Adequate residual plot created; reasonable explanation of how to improve the linear regression
model based on interpretation of the plot. Reasonable explanation of department qualification
for additional state funding, includes limitations, mostly based on linear regression analysis.
0
F – 1 – No Pass
Adequate residual plot not created or created with errors; unclear or limited explanation of how
to improve the linear regression model or explanation not clearly based on interpretation of the
plot. Unclear or limited explanation of department qualification for additional state funding;
does not include limitations, or is not based on linear regression analysis.
0
I – 0 – Not Submitted
Not Submitted
0
•
Criterion 5
0% of total grade
A – 4 – Mastery
Adequate comparative matrix conducted for sectors; advanced explanation of how findings
impact operations. Thorough description of precautions or behaviors that should be exercised
when working with and communicating about sensitive data.
0
B – 3 – Proficiency
Adequate comparative matrix conducted for sectors; strong explanation of how findings impact
operations. Strong description of precautions or behaviors that should be exercised when
working with and communicating about sensitive data.
0
C – 2 – Competence
Adequate comparative matrix conducted for sectors; reasonable explanation of how findings
impact operations. Adequate description of precautions or behaviors that should be exercised
when working with and communicating about sensitive data.
0
F – 1 – No Pass
Comparative matrix for sectors conducted with errors; unclear or limited explanation of how
findings impact operations. Limited or inaccurate description of precautions or behaviors that
should be exercised when working with and communicating about sensitive data.
0
I – 0 – Not Submitted
Not Submitted
0
•
Criterion 6
0% of total grade
A – 4 – Mastery
Thorough and detailed discussion of additional tools or technologies that could impact data
collection, storage, or analysis for future projects. Used and relied on all credible sources in a
well-crafted report.
0
B – 3 – Proficiency
Substantial discussion of additional tools or technologies that could impact data collection,
storage, or analysis for future projects. Used and relied on mostly credible sources in the report.
0
C – 2 – Competence
Moderate discussion of additional tools or technologies that could impact data collection,
storage, or analysis for future projects. Used and identified some credible sources in the report.
0
F – 1 – No Pass
Somewhat extensively discussed additional tools or technologies that could impact data
collection, storage, or analysis for future projects. Failed to use or identify credible sources in
the report.
0
I – 0 – Not Submitted
Not Submitted
0