Real Estate: Property Price Prediction Workflow

PredictModel provides a comprehensive AWS-based solution to forecast property prices, designed to assist real estate companies and investors in making informed decisions. Our robust data engineering and machine learning platform gives users the tools necessary to predict future property values effectively, ensuring smarter investments.

Amazon S3
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AWS Glue
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Amazon Redshift
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Amazon SageMaker
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AWS Lambda

Workflow Step Explanation

  1. Data Storage: Amazon S3 serves as the initial data lake for storing raw property data from various sources such as listings, market trends, and historical sales.
  2. Data Processing: AWS Glue is responsible for ETL (Extract, Transform, Load) operations that clean and prepare data for further analysis.
  3. Data Warehousing: Amazon Redshift provides a data warehouse for storing structured data and allows complex queries and analysis on large scale datasets.
  4. Machine Learning: Amazon SageMaker is used to build, train, and deploy machine learning models that forecast future property prices based on historical data and other predictors.
  5. Automation: AWS Lambda automates the execution of models and other operational tasks, triggering actions based on event-driven architectures.