Emergency Call Data Analysis

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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.

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.

 

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. Table: number of incident occurrences by event type OR

d. Bar graph: number of incident occurrences by event type

 

e. Table: sectors and number of events OR

f. Bar graph: sectors and 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.

 

 

Sample Solution

  1. Prepare the dataset. This involves removing any potential errors or outliers, duplicate records, or data that are not necessary. To do this, I would first identify any cells that contain errors or outliers. I would then remove these cells from the dataset. I would also remove any duplicate records from the dataset. Finally, I would remove any data that is not necessary for the analysis.
  2. 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. For each column or row that I removed, I would explain why I removed it. For example, if I removed a column because it contained errors, I would explain the nature of the errors and why they needed to be removed. If I imputed data in an empty field, I would explain why I did so and how I imputed the data.
  3. Create data sheets using your cleaned dataset and provide each of the following to represent the requested aggregated data. The requested aggregated data includes:
    • A table of the date and number of events.
    • A bar graph of the date and number of events.
    • A table of the number of incident occurrences by event type.
    • A bar graph of the number of incident occurrences by event type.
    • A table of the sectors and number of events.
    • A bar graph of the sectors and number of events.
  4. 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. In this section, I would summarize my observations from the datasheets. I would look for trends and patterns in the data. I would also identify any areas where further analysis is needed.

Here is an example of how I would summarize my observations from the datasheets:

  • The number of 911 calls has been increasing over the past year.
  • The most common type of 911 call is for medical assistance.
  • The number of calls for fire assistance has been decreasing over the past year.
  • The majority of 911 calls are made during the day.
  • The sectors with the most 911 calls are downtown and the west side of the city.

I would then use these observations to inform my analysis in Part 2.

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