Difference between revisions of "Hiryuu Project Management"

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==<div style="background: #A4A4A4; line-height: 0.3em; font-family:Roboto;  border-left: #848484 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#ffffff"><strong>Scope of Work</strong></font></div></div>==
 
==<div style="background: #A4A4A4; line-height: 0.3em; font-family:Roboto;  border-left: #848484 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#ffffff"><strong>Scope of Work</strong></font></div></div>==
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<ol>
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<li><b>Data Gathering and Scoping</b></li>
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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.
  
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#Data Gathering and Scoping
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<li><b>Research on Software and Proposal Preparation</b></li>
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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.
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Our team has researched and discussed on the software and applications used in analysing and visualising the data with our supervisor and sponsor.
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<p>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.</p>
  
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#Research on Software and Proposal Preparation
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<p>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.</p>
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Our team has researched and discussed on the software and applications used in analysing and visualising the data with our supervisor and sponsor.
 
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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.
 
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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.
 
  
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#Data Cleaning and restructuring
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<li><b>Data Cleaning and restructuring</b></li>
 
<p>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. </p>
 
<p>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. </p>
  
 
<p>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. </p>
 
<p>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. </p>
  
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#Data Modelling
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<li><b>Data Modelling</b></li>
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# a.Exploratory Analysis
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<ol type="a">
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# b.Geospatial Analysis
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<li>Exploratory Analysis</li>
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# c.Clustering
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<li>Geospatial Analysis
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# d.Time Series Data Analysis
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<li>Clustering
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<li>Time Series Data Analysis
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</ol>
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</ol>
  
 
==<div style="background: #A4A4A4; line-height: 0.3em; font-family:Roboto;  border-left: #848484 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#ffffff"><strong>Timeline</strong></font></div></div>==
 
==<div style="background: #A4A4A4; line-height: 0.3em; font-family:Roboto;  border-left: #848484 solid 15px;"><div style="border-left: #FFFFFF solid 5px; padding:15px;font-size:15px;"><font color= "#ffffff"><strong>Timeline</strong></font></div></div>==

Revision as of 00:45, 16 January 2017

Current Project

Logo Hiryuu.png


Home

About Us

Project Overview

Findings

Project Management

Documentations

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.
  2. Research on Software and Proposal Preparation
    3. 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.

  3. Data Cleaning and restructuring

    4. 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.

  4. Data Modelling
    1. Exploratory Analysis
    2. Geospatial Analysis
    3. Clustering
    4. Time Series Data Analysis

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 In Progress
Resolve/remove incomplete data Week 1 Week 2 All In Progress
Data Modelling
Stage 1: Exploratory Analysis Week 3 Week 6 All Not Completed
Stage 2: Clustering Week 3 Week 6 All Not Completed
Stage 3: Time Series Analysis Week 3 Week 6 Jouta Not Completed
Stage 4: Geospatial Week 5 Week 10 Qianpin Not Completed
Interim Preparation
Gather feedback from Client Week 4 Week 8 All Not Completed
Prepare interim report and slides Week 6 Week 7 Jouta Not Completed
Application Building
Code the application Week 8 Week 11 All Not Completed
Testing the application Week 10 Week 12 All Not Completed
Gather feedback from Client Week 12 Week 16 All Not Completed
Iteration
Adjust analysis Week 12 Week 13 Jouta Not Completed
Refine results to improve clarity Week 12 Week 13 Wan Theng, Qianpin Not Completed
Final Preparation
Prepare Research Paper Week 14 Week 14 All Not Completed
Prepare Poster Week 15 Week 15 Qianpin Not Completed

Work Plan

  • Fortnightly meetings with Supervisor
  • Monthly meetings with Sponsor
Hiryuu Gantt Chart.JPG
Retrieved from ‘https://wiki.smu.edu.sg/ANLY482/index.php?title=Hiryuu_Project_Management&oldid=12847’