Fashion: Demand Forecasting Workflow

PredictModel offers an advanced AWS-based solution tailored for the fashion industry to accurately predict product demand. This powerful data engineering and machine learning platform empowers fashion brands to optimize inventory management, reduce waste, and drive sales with precise demand forecasting.

Amazon S3
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AWS Glue
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Amazon Redshift
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Amazon Forecast
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AWS Lambda

Workflow Step Explanation

  1. Data Storage: Amazon S3 acts as the primary data lake, storing raw sales, inventory, and market trend data from multiple sources.
  2. Data Processing: AWS Glue handles ETL (Extract, Transform, Load) operations to clean and prepare data for subsequent analysis.
  3. Data Warehousing: Amazon Redshift serves as the data warehouse for storing structured data and enables complex queries and analysis on large datasets.
  4. Machine Learning: Amazon Forecast is used to train and deploy machine learning models that predict future product demand based on historical sales, trends, and other relevant factors.
  5. Automation: AWS Lambda automates the entire process, including data updates, model retraining, and deploying predictions to relevant applications.