Property Wealth Advisory

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Assignment tasks/description (Max 1500 Words)

Property Wealth Advisory (PWA)

Property Wealth Advisory (PWA) is a boutique client-focused property investment advisory.  PWA provides advice and market research on property investments specializing joint owned property investments for clients looking to diversify their portfolio. The company also cater for individuals who are seeking to be a home-owner in the right locations.

The service offered by PWA is considered a premium in Australia. The recommendations made by PWA is based on real estate data carefully curated through various means, including data from Consumer Affairs Victoria, Domain.com.au, PropertyData.com.au, and PropertyValue.com.au. The company often advertised its ability to select properties in areas that deliver strong yields with minimum risk (i.e., capital growth in a high-growth area), and/or have the potential for added value to increase future returns (i.e., sizeable land for future development).

PWA operates in three states: Queensland, Victoria, and New South Wales. The backbone of the operations is a small team of young and talented analysts located in PWA’s main office in Hawthorn, Victoria. The analysts’ role is to go through the real estate data and write a report on the trends, key indicators, market forecasting, and other valuable insights emerging from the data.

A New Team Member

You just accepted a job offer as an analyst for PWA. As a new member, you are still on one year probation. You need to demonstrate your value to the company by showcasing your ability to make sense and/or analyse data and produce some relevant insights before you can join the A-team (the main analyst team which is the backbone of PWA business).

Your Tasks

You have been given some tasks to provide a report based on the Melbourne Real Estate Market Data. You are to produce a brief report containing analyses of:

  1. The quality of the dataset: clearly and systematically addressing the quality issues in the dataset, whether the issue(s) is significant enough for the purpose of  further analysis, and more importantly, how you would approach the shortcomings in the dataset;
  2. Using your data analytics skills, provide 6 interesting insights based on descriptive analytics of the data. You get to determine which area you want to showcase. However, you need to be able to articulate as to why your chosen insights would be of interest and of value to a property investor (i.e., PWA client). Remember, you are to showcase “insights” from your analysis of the data, not merely describing the numbers. Each of the insights need to be supported by appropriate data visualizations;
  3. Based on your understanding of the data, provide between 3-5 recommendations for further data enrichment to enhance and facilitate more advance analysis. Remember, the recommendations for data enrichment needs to be sensible and viable;

 

Deliverables: 

  1. A Report containing the data quality assessment, the insights, and the recommendations (+ references/reference list and appendix where appropriate)
  2. Tableau workbook package file (i.e., .twbx) containing the worksheets/dashboards for the Part A.

 

Melbourne Real Estate Market Data

Our Data Technician has scraped 3 years data on Melbourne Real Estate Market. The 2020-2022 data should be adequate to allow you to conduct meaningful analysis of the data and write a report. The data technician acknowledges there may be missing values and/or inconsistent values in the dataset.

As per usual, the dataset has been uploaded in PWA central repository (a.k.a., INF30004 Canvas site) for your access: Melbourne REM 2020-2022 Dataset

In order to help your team making sense of the data, the following data dictionary is provided.

Suburb Suburb
Address Address
Rooms Number of rooms
Price Price in Australian dollars
Method S – property sold
SP – property sold prior
PI – property passed in
PN – sold prior not disclosed
SN – sold not disclosed
NB – no bid
VB – vendor bid
W – withdrawn prior to auction
SA – sold after auction
SS – sold after auction price not disclosed
N/A – price or highest bid not available
Type br – bedroom(s)
h – house,cottage,villa, semi,terrace
u – unit, duplex
t – townhouse
dev site – development site
o res – other residential
SellerG Real Estate Agent
Date Date sold
Distance Distance from CBD in Kilometres
Regionname General Region (West, North West, North, North east …etc)
Propertycount Number of properties that exist in the suburb
Bedroom # of Bedrooms
Bathroom # of Bathrooms
Car Carport size/capacity
Landsize Land Size in Metres
BuildingArea Building Size in Metres
YearBuilt Year the house was built
CouncilArea Governing council for the area
Latitude Latitude
Longitude Longitude

 

 

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