Overview For This Assignment You Are Responsible For Designi

Overviewfor This Assignment You Are Responsible For Designing A Visua

Overview for this assignment, you are responsible for designing a visual project in Power BI where you explain and examine an open source data set retrieved from either the NT Government Open Data Project or the Darwin City Council. Your task involves selecting two data sets, formulating relevant analytical questions, extracting and visualizing data to answer these questions, and discussing the insights gained. The project should culminate in a report with appropriate visualizations, analysis, and ethical considerations, demonstrating your proficiency in data analysis, visualization, and Power BI skills.

Paper For Above instruction

The objective of this assignment is to develop a comprehensive understanding of how to effectively analyze and visualize open source data using Power BI. The process begins with selecting two relevant data sets, preferably from sources such as the NT Government Open Data Project or Darwin City Council, which provide rich and diverse datasets suitable for analysis. The choice of data sets should align with the questions you intend to explore and the audience you aim to engage.

The first crucial step involves framing three pertinent questions related to the data. These questions should be designed to extract meaningful insights while considering the target audience’s interests and needs. As a data analyst, your questions might focus on identifying trends, patterns, or anomalies within the data. The questions could include inquiries about demographic distributions, service usage patterns, environmental impacts, or other relevant themes depending on the datasets chosen.

Following the formulation of questions, the next phase involves data wrangling. This step includes cleaning the data—handling missing values, correcting inconsistencies, and transforming data into suitable formats. Understanding the structure and content of the datasets through exploratory analysis is essential to identify features that will support answering your questions. For example, selecting relevant nominal and numeric data, and computing descriptive statistics such as mean, maximum, minimum, or mode, helps in clarifying the data’s story.

In designing visualizations, selecting appropriate graphical representations is vital. Charts such as bar graphs, line graphs, heat maps, or scatter plots can effectively convey different types of information. The choice of visual encoding—such as color, size, or interaction—should enhance comprehension and engagement, tailored to your audience. Testing whether the visualizations can answer the initial questions is an important validation step.

The analysis is strengthened by ensuring visual clarity and relevance. Briefly interpreting the visualization outputs allows you to derive insights—for instance, identifying regions with high environmental impact or demographic clusters. The visualizations should tell a compelling story that addresses your original questions, supports decision-making, or highlights key trends.

The report should be structured to include the following sections:

  • Problem Statement: Clarify the problem you aim to solve with the data, outlining the three questions and the intended audience.
  • Data Wrangling: Describe the cleaning and understanding processes applied to the datasets.
  • Features Extracted: List and justify the selection of features used for analysis.
  • Ethical Considerations: Discuss relevant ethical issues, guided by the Business Ethics Canvas, such as data privacy, bias, and responsible use.
  • Modelling & Analysis: Explain the visualization and statistical methods employed, including why these methods are suitable.
  • Results Presentation: Showcase your Power BI dashboard with visualizations, numerical summaries, and textual insights. Critically reflect on your visualization choices.

This assignment assesses your data analysis skills, ability to utilize Power BI effectively, capacity for statistical thinking, and your written communication skills. Your report should be clear, insightful, well-structured, and demonstrate originality in approaching the problem.

References

  • Shmueli, G., Bruce, P. C., Gedeck, P., & Gedeck, P. (2020). Data Science for Business. Springer.
  • Kelleher, J., & Tierney, B. (2018). Data science fundamentals in Power BI. Microsoft Press.
  • Hevner, A. R., March, S. T., Park, J., & Ram, S. (2004). Design science research in information systems research. MIS Quarterly, 28(1), 75-105.
  • Evergreen, S. (2017). Presenting Data Effectively: Communicating Your Findings for Maximum Impact. Sage Publications.
  • Few, S. (2012). Show Me the Numbers: Designing Tables and Graphs to Enlighten. Analytics Press.
  • Yau, N. (2013). Data Points: Visualization That Means Something. Wiley.
  • Roberts, J., & Hann, I. (2020). Ethical considerations in data science. Journal of Business Ethics, 162(3), 519-531.
  • Business Ethics Canvas. (2018). Harvard Business Publishing.
  • Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137-144.
  • Heerschap, W. (2019). Visualize This: The Flowing Data Guide to Design, Visualization, and Statistics. O'Reilly Media.

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