Ascendion’s experience in deep data engineering expertise (DataOps and MLOps) helped us leverage modern data strategies and drive technology expertise. We used ASCENDION AVA+ ML Optimization studio and implemented Databricks MLOps with a MLFlow solution. Our solution included using forecast models such as ARIMA, Prophet, exponential smoothing, and XGBoost within a unified framework.
Ascendion deployed MLFlow’s tracking capabilities to enable easy comparison and evaluation of the forecast models. With monitoring and logging mechanisms implemented, we tracked the performance of the deployed models.
Our solution provided automation and continuous integration to refine and enhance the models (based on user feedback and factors such as weather and traffic), optimize resource allocation and inventory, identify bottlenecks, and reduce delivery delays, resulting in improved customer satisfaction.