CASE STUDY
The client relied on traditional data science methods for demand forecasting.
These traditional methods failed to capture complex data patterns.
The client struggled to balance inventory levels effectively.
Inefficient inventory management led to increased costs and lost revenue.
40%
10-20%
15-30%
Solutions
Created feature stores by extracting the data from the data lakehouse.
Leveraged statistical models like ARIMA, SARIMA and Deep Learning Time Series models.
Created an optimization layer for inventory management.
Developed intuitive dashboards and visualization tools for stakeholders
Congratulations and a big thank you to everyone that successfully implemented our demand forecasting solution. The team did a great job ensuring that our upgrades did not compromise operations or result in excess costs.
Sr. Data Lead
$50,000 - $1,00,000
Saved Annually
Audience
- Executives, CTOs, Director
- IT Consultants
- Business Analysts
- Project Managers
- IT Project Coordinators
- Architects and Specialists
