Group02 proposal

Team

Proposal

Poster

Application

Research Paper

PROBLEM & MOTIVATION

Problem
When it comes to purchasing or renting a property, there are many factors that go into a buyer’s consideration before he makes the final decision. The primary concern for buyers is the pricing of the property [1].

However, our group identified that there are also secondary concerns such as the weather and the amenities available that do influence the buyer’s final decision to purchase the property.

There are limited tools available to help property buyers to identify areas that suit their needs/preferences best. The current tools that are available are only optimal to suit one category of concern, but fails when we try to use more categories to make our visualization.

For example, different people have different preferences for the weather. Some may prefer sunny weather while others prefer it to rain all the time. Currently, we are able to find weather information, and property prices information, but not both at the same time.

Motivation
Through the visualization, our group hopes to be able to better allow for users to be able to visualize a home of his dreams beyond mere price.

OBJECTIVES

Target Group:

DATASET

Data/Source	Variables/Description	Methodology

BACKGROUND SURVEY OF RELATED WORK

Reference of Other Interactive Visualization	Learning Points
Title:
Title:
Title:
Title:

REFERENCE LIST

References

KEY TECHNICAL CHALLENGES & MITIGATION

No.	Challenge	Description	Mitigation Plan
1.	Software Challenge	Unfamiliarity of visualisation tools such as R, R Shiny, Tableau.	Github Learning Stackoverflow research Self-directed and peer learning Watch video tutorials from YouTube Hands-on practice using the different training platforms such as Data Camps
2.	Programming Challenge	Inexperince with data cleaning and transformation using R	Trial and error Read online articles and forums for guidance Watch video tutorials on how to fully utilise packages such as lapply, tidyr and dplyr
3.	Workload Constraint	Time and Workload Constrains	Design reasonable project timeline based on everyone's ability and capacity. Set milestones and adjust the timeline accordingly based on the team's progress.
4.	Dataset Complexity	Our have different data from multiple sources in multiple different formats, hence we foresee a huge challenge in standardizing the data Note: Our current dataset is looking at 49 areas over the spread of 8 years of data, for every year there are 12 months of data. This gives a total of 4,704 CSV files to consolidate and clean for weather data alone.	Make use of data preparation tools such as tableau prep Make use of our database management skills to normalize all data tables into third normal form

STORYBOARD

Dashboards	Description
Dashboard 1:	Description 1 Description 2 Description 3
Dashboard 2	Description 1 Description 2 Description 3
Dashboard 3:	Description 1 Description 2 Description 3

COMMENTS

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