Client Overview
For one of the World’s Largest Manufacturer of Tires.
Challenge
The client wanted to develop Machine learning algorithm to near-accurate predict deployment of inventory from Hub to its various distribution centers.
Solution
The logic of distributing inventory to distribution centers will depend upon analyzing multiple datasets and to find a correlation of data using machine learning models to predict the outcome.
- Data ingestion, cleaning, and transformation to be done through ETL scripts ( SSIS packages)
- Cleaned data uploaded in SQL Server Data warehouse
- Machine learning models to run on cleaned and stitched data. Various machine learning forecasting/regression models implemented on data and results accuracy and validations checked to arrive at an optimized model