Conversation with Merlin [email protected] · Sat Dec 16 2023

Consider that you are a Lead Data Analyst at a Real Estate company in Boston that has provided you with the House Pricing dataset. You have been given a task to explore the data, create different plots and interpret useful insights/findings. Your end goal here will be to create a storyboard that you have to present to the Senior Management and the story has to have an end objective and should follow a logical flow to display that you are heading towards achieving the end objective. This will help the Senior Management in taking some decisive actions on the current House Recommendation System in place. This storyboard will be an open-ended story for you to explore various different features in the data and try to showcase different plots. Make sure to have minimum clutter in the plots, follow a consistent color scheme across all the plots, and use proper colors to highlight a specific insight. Moreover, your plots on all the dashboards should be interactive and responsive. There should be 1 dashboard that should cover the summary of the story as well as your recommendations.

To begin with the exploration of the House Pricing dataset, I will first conduct a basic review to understand the structure and contents of the dataset. Once I have a good grasp of the data, I will to identify key features and trends that will help in making informed for the improvement of the House Recommendation System.

Dashboard 1: Overview and Initial Insights

  1. Title: Exploring the House Dataset

    Description: This dashboard will provide an overview of the dataset, highlighting key statistics and distributions of important variables.

. Summary and Initial Insights

  • Showcase the distribution of house prices in Boston.
  • Highlight the distribution of important features such as square footage, number of bedrooms, and number of bathrooms.
  • Explore any notable trends or correlations between features.
  • Aim to identify any outliers or anomalies that may impact the analysis.

Dashboard 2: Location-Based Analysis

  1. Title: Location Matters: Exploring Geographic Trends

    Description: This dashboard will focus on the geographic aspects of house pricing, aiming to uncover insights related to and its impact on house prices.

  2. Location-Based Insights

    • Utilize interactive maps to visualize the distribution of house prices across different neighborhoods in Boston.
    • Highlight any areas with particularly high or low average prices.
    • Explore trends related to proximity to amenities, schools, and public transportation.

Dashboard 3: Time Trends and Seasonal Patterns

  1. Title: Uncovering-Based Patterns

    Description: This dashboard will delve into historical data to identify time-based trends and seasonal patterns that may impact house pricing.

  2. Time-Based Insights

    • Present interactive time series plots to showcase how house prices have evolved over different years.
    • Identify seasonal variations in house.
    • Correlate seasonality with specific features such as property size, location, or property type.

Dashboard 4: Preferences and Demand

  1. Title: Understanding Customer Preferences

    Description: This dashboard will focus on capturing insights related to customer preferences and demand, to understand what features are most influential in the decision-making process.

  2. Customer Preferences Insights

    • Utilize interactive visuals to showcase the distribution of features such as nearby amenities, property age, and property types.
    • Analyze how these features impact house pricing and demand.
    • Identify key factors that are most influential in customer decision-making.

Dashboard 5: Final Recommendations and Conclusions

  1. Title: Actionable Insights and Recommendations

    Description: This will summarize the key findings and insights gathered from the analysis, providing actionable recommendations for the improvement of the House Recommendation System.

  2. Recommend and Conclusions

    • Summarize the most impactful insights gathered from the analysis.
    • Provide data-driven recommendations for the current House Recommendation System.
    • Emphasize the new features or data points that should be integrated into the recommendation system to improve its accuracy and effectiveness.

This comprehensive storyboard will follow a logical flow, ensuring the exploration of the dataset generates actionable insights and valuable recommendations for the Senior Management to make informed decisions regarding the House Recommendation System.