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Crime Data Visualisation Assignment: US Crime Case Study for Law Enforcement Intelligence
| University | Brunel University London (BUL) |
| Subject | Crime Analysis |
This coursework assesses the following course learning outcomes:
- Define, demarcate and explore business problems interactively in communication with key stakeholders – MO1.
- Select, evaluate and employ appropriate tools, platforms and methods to generate BI and visualisation solutions – MO2.
- Reflect upon, critique and improve upon own and others informational and visual artefacts – MO3.
- Deliver a data-driven narrative appropriately and effectively to stakeholders, based on a theoretical underpinning of communicating for impact – MO4.
The coursework is worth 50% of the overall mark for the module.
Broadly speaking, the coursework requires you to undertake a business intelligence project and document the evolution of the project through a reflective diary. The project will involve taking a dataset, exploring the data and developing a report that tells a specific data-driven narrative using various visualisations. The reflective diary will describe the process followed and decisions taken with justifications. The reflective diary should consist of approximately 4000 words, which may include screenshots and diagrams. The coursework is described in more detail in section 2.
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This is an individual coursework, you will be writing individual reflective diary. Working on this assignment will help you to practice problem solving skills, management skills, communication skills. From a business intelligence and data visualisation perspective, you will practice data processing/analysis, pattern discovery, as well as visual storytelling and effective communication.
Crime analysis is one of the most important activities that intelligence and law enforcement organisations perform all over the world. In this project you will analyse data that has been collected about crimes that happened in different parts of the US. The dataset consists of all related data about a crime such as where it happened, the important dates of the event and how is it co related to other events. Most law and enforcement agencies face the challenge of efficiently and accurately analysing the growing volume of crime-related data.
The outcome of the project will show useful insights such as:
Below is a list of recommended milestones that will guide you throughout your project. You can document your progress through these milestones in your reflective diary and submit it as evidence of having met these milestones.
Explore and familiarise yourself with the dataset. Some questions you can explore are:
- Does the dataset need cleaning?
- Does the dataset have any missing values that need to be handled?
- Does it need any other kind of pre-processing?
- How has the data been compiled/calculated?
- Are there any extra fields/calculations that could be added to make understanding the data easier?
- What are the characteristics of the data?
Summarising the data in various ways may help.
Analysing and understanding complex patterns of crimes.
- What are the trends in the progression of crimes in certain areas?
- What age groups are mostly involved in these incidents?
- What weapons are used in various crimes?
- What measures can law enforcement agencies take to reduce crime?
Below is a list of recommended milestones that will guide you throughout your project. You can document your progress through these milestones in your reflective diary and submit it as evidence of having met these milestones.
Explore and familiarise yourself with the dataset. Some questions you can explore are:
- Does the dataset need cleaning?
- Does the dataset have any missing values that need to be handled?
- Does it need any other kind of pre-processing?
- How has the data been compiled/calculated?
- Are there any extra fields/calculations that could be added to make understanding the data easier?
- What are the characteristics of the data?
Summarising the data in various ways may help.
Identify appropriate visualisations that would help answer the business questions.
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Create prototypes of the visualisations.
Identify appropriate visualisations that would help answer the business questions.
Create prototypes of the visualisations.
Make some recommendations that can help improve the outcomes for the stakeholders. For example:
- How can UWE improve its position in the future?
- How can the North American retailer improve their sales in the future?
- What measure can help law enforcements agencies reduce crime?
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