We have enhanced the Victoria Property Market dataset by addressing issues with quality and emphasizing "Price Trends and Property Types." We provided insights into property distribution, price trends, and location-price correlations using visualizations. To help investors make wise judgements, we recommended imputed missing price data and augmenting the information with economic indicators and property amenities. The Victoria Real Estate Insights Consortium (V-REIC) INF70008 BA Project Report Amisha Gadekar
14 Business Analytics and Visualization INF70008
14 Business Analytics and Visualization INF70008 Assessment of Dataset Quality- The quality of datasets plays a crucial role in the ever-evolving landscape of data- driven decision-making. This is especially important for organizations like The Victoria Real Estate Insights Consortium (V-REIC), which rely on accurate and clean data to analyze and make informed decisions. Having access to the Victoria region's real estate transaction information requires V-REIC to adhere to the highest standards of dataset quality in order to ensure its insights are trustworthy. "Victoria Property 2020-2022," the dataset made available by V-REIC, contains a wide range of statistics on real estate transactions. Important information about each property is included in this dataset, including the property's unique identifier, address, suburb, type, price, status, date of record, and a variety of attributes, including the number of bedrooms and bathrooms, the number of garage spaces, the size of the land, the building's area, and more. Latitude and longitude are also given, which increases the spatial significance of the dataset. Additional data is provided alongside the property dataset in the "RE Agents" and "Vic Regions-Suburbs" tables. The former offers information on the real estate brokers in charge of property sales, while the latter adds context by providing information on the suburbs in the Victoria region, such as property counts and council names. Identify Dataset Issues- 1. Inconsistent Property Types: The "Prop Type" field has codes for different property types (h-house, home, t-townhouse, unit and u-unit/flat/apartment). Inconsistent or unclear coding could lead to incorrect categorization of properties. 2. Potential Outliers: The "Price," "Landsize," and "Building Area" fields contains outliers that could affect statistical analyses and visualization interpretations.