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This piece of work looked at house prices in the real estate world from 1990 to 2010. It provided insights into factors that influence price and forecast sales trends. This is part of volunteer work.

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IsaacSantous/House-Price-Prediction-Leveraging-Tableau

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BUSINESS INTRODUCTION
Blue Ark Reality is a leading real estate company dedicated to helping clients find their dream homes. Blue Ark Reality's commitment to client satisfaction extends beyond just buying and selling houses — they aim to create communities where families can thrive. The business uses data-driven insights to stay ahead by leveraging advanced analytics and visualization tools like Tableau, to optimize operations and provide their clients with a seamless experience.
PROBLEM STATEMENT
The real estate market is inherently volatile and influenced by a variety of factors such as location, quality of materials, and market conditions. Traditional methods often fail to capture the nuanced patterns contributing to price fluctuations. The challenge lies in observing these patterns and predicting future outcomes using historical and current data to provide accurate insights into house prices.
RATIONALE FOR THE PROJECT
Accurately predicting house prices is crucial for making informed decisions in the real estate market. This project is significant because it enables stakeholders to understand the underlying factors affecting house prices, improving their ability to navigate the market confidently. The use of Tableau allows for powerful data visualization, transforming complex data into actionable insights.
AIM OF THE PROJECT
• Develop an interactive Tableau dashboard that visualizes key real estate metrics.
• Enable users to explore relationships between various factors (e.g., quality, location) and house prices.
• Enhance decision-making capabilities for real estate professionals by providing actionable insights from analysis.
• Create a forecast using historical data to estimate future house prices.
• Analyze data on real estate sales and observe patterns and trends within the data.
DATA DESCRIPTION
The dataset includes a variety of variables essential for understanding house prices, such as Sale Price, Neighbourhood, Year Built, Overall Quality, and more. Each variable provides insights into different aspects of the housing market, allowing for a comprehensive analysis.
EXPLORATORY DATA ANALYSIS WITH TABLEAU
• Before starting with EDA, I checked and explored the data for missing values, misspelt data, blanks, etc.
• Connected the Tableau desktop to the data source that contains the house price prediction data.
• Joined the different tables/sheets
• No missing values were identified. Hence, I commenced the analysis.
KEY METRICS
• Number of Houses Sold
• Revenue Generated
• Factors Influencing Sales
• Relationships in Data
• Sales Price Predictions
TECH STACK
• Data Structuring
• Calculated Fields
• Visualizations
• Filters and Parameters
KEY INSIGHTS
• Blue Ark Reality sold 1,460 houses from 2006 to 2010; this generated a total revenue of USD 264 million.
• 1 story and 2 story house style are the most marketed houses.
• 3 bedrooms followed by 2 bedrooms are the most sold houses for dwelling.
• Neighbourhoods influence the average price of houses as revealed by the data.
• Remodelling of houses leads to a higher price sale as seen from 2004 to 2010.
• The overall material and finish quality of houses is a great deal in determining house price.
• Warranty Deed is the most used sale type – a method where the grantor (seller) guarantees that they hold clear title to a piece of real estate and has a right to sell it to the grantee (buyer).
• There were price fluctuations from January 2006 to June 2010 but a pick in price is constantly observed between June and July of the same period.
• The forecast predicted a sale pick in July 2010, this will slow down in August of the same year and pick again in July 2011.
CONCLUSION
Blue Ark Reality should invest more in three-bedroom and two-bedroom houses. When investing in real estate the neighbourhood, house style, quality of material and finish quality are factors to consider. These factors determine the price of the house. June and July have been identified as the pick months for real estate, this is supported by data from 1990 to 2010, which is also seen in the forecast. Blue Ark should take advantage of these months and the factors influencing sales. Warranty Deed is a better method to sell properties.

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This piece of work looked at house prices in the real estate world from 1990 to 2010. It provided insights into factors that influence price and forecast sales trends. This is part of volunteer work.

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