/on-shelf-availability

This Solution Accelerator shows how OOS can be solved with real-time data and analytics by using the Databricks Lakehouse Platform to solve on-shelf availability in real time to increase retail sales. The accelerator can also be used for supply chain solutions.

Primary LanguagePythonOtherNOASSERTION

on-shelf-availability

To run this accelerator, clone this repo into a Databricks workspace. Attach the RUNME notebook to any cluster running a DBR 11.0 or later runtime, and execute the notebook via Run-All. A multi-step-job describing the accelerator pipeline will be created, and the link will be provided. Execute the multi-step-job to see how the pipeline runs.

The job configuration is written in the RUNME notebook in json format. The cost associated with running the accelerator is the user's responsibility.