Hiryuu Project Management

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Project Overview

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Project Management

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Overview

Scope of Work

  1. Data Gathering and Scoping
  2. Data have been gathered from our sponsor which consists of data across 3 months and spanning across several countries. The data given to us are all in .csv formats.
  3. Research on Software and Proposal Preparation
  4. Our team has researched and discussed on the software and applications used in analysing and visualising the data with our supervisor and sponsor.

    We will mainly utilise JMP Pro for the clustering, exploratory, and seasonality analysis and QGIS for our geospatial analysis. Our sponsor has expressed their preference for the final product to be in Power BI as they are familiar with it. In addition, they have expressed interest for the final product to be dynamic, meaning any input of future data can tap on the methods used to produce the results.

    Currently we will focus on analysis on JMP Pro and QGIS and have plans to decide how to compromise the dynamic capabilities within our limitations.

  5. Data Cleaning and restructuring
  6. After looking and familiarising ourselves with the data, we discovered the complexity of the data. The data is not only large in size, contains a wide variety, and also inconsistent across different countries. This inconsistency is due to the differences in language used for reporting as well as different systems used. As such, certain coding languages could not be used to process the values and other solutions have to be looked into.

    Due to the complexity and variety of the data, we will be conducting data cleaning by removing duplicates, ensuring consistency by inserting the header column, merging the data files, filtering the data by countries and checking that the data is appropriate and ready for analysis.

  7. Data Modelling
    1. Exploratory Analysis
    2. Geospatial Analysis
    3. Time Series Data Analysis
  8. Dashboard Building
  9. To offer a dynamic dashboard that can intake raw data from the providers and produce meaningful graphs and charts for the user to understand the logistics performance, we decided to utilise Rshiny. Both service providers engaged very different in their data collection, hence we decided to build 2 separate dashboards to handle the 2 very different formats. However, our delivery of analysis is similar for both dashboards. We were able to build the dashboard with a clearer end picture in mind as we had a c better understanding of the data after the earlier analysis done on JMP Pro.

Timeline

Tasks Start End Teammates Involved Status
Data Gathering and Scoping
Gather Data Week 0 Week 0 All Completed
Finalise Requirements with client Week 0 Week 0 All Completed
Scope Project Week 0 Week 0 All Completed
Research and Preparation
Explore software Week 0 Week 0 All Completed
Finalise Proposal Week 0 Week 0 All Completed
Create and update wiki page Week 0 Week 0 All Completed
Data Cleaning
Data collection Week 1 Week 2 All Completed
Data cleaning and restructuring Week 1 Week 2 All Completed
Resolve/remove incomplete data Week 1 Week 2 All Completed
Data Modelling
Analysis 1: Exploratory Analysis Week 3 Week 8 All Completed
Analysis 2: Time Series/Seasonality Week 6 Week 9 Wan Theng Completed
Analysis 3: Geospatial Analysis Week 4 Week 13 Qianpin Completed
Interim Preparation
Gather feedback from Client Week 4 Week 8 All Completed
Prepare interim report and slides Week 7 Week 8 Jouta Completed
Application Building
Code the application Week 6 Week 14 All Completed
Testing the application Week 10 Week 14 All Completed
Gather feedback from Client Week 12 Week 16 All Completed
Iteration
Adjust analysis Week 12 Week 13 Jouta Completed
Refine results to improve clarity Week 12 Week 13 Wan Theng, Qianpin Completed
Final Preparation
Prepare Research Paper Week 14 Week 14 All Completed
Prepare Poster Week 15 Week 15 Qianpin Completed

Work Plan

  • Fortnightly meetings with Supervisor
  • Monthly meetings with Sponsor
Hiryuu Gantt Chart.JPG

Final Changes:

  • Clustering module removed
  • Exploratory Analysis completed by Week 8
  • Time Series completed by Week 9
  • Geospatial Analysis completed by Week 14
  • Both Rshiny dashboards completed by Week 15
  • Dummy Data created for poster session