Graph Analytics for Telco Customer Churn Prediction

https://www.databricks.com/solutions/accelerators/graph-analytics-telco-customer-churn-prediction

By leveraging the inherent relationships and connections in the network, graph analytics can provide valuable insights into customer behavior and interactions, enabling more accurate churn prediction and proactive retention strategies. This Solution Accelerator walks you through how to engineer call network graph features and analyze them using a machine learning model. ML models can predict customer churn by analyzing call network graph features together with other customer features, identifying influential customers based on their central or connected position in the network. Use this Solution Accelerator to:

* Analyze call network graphs at scale with Apache Spark™ GraphFrames
* Manage telco customer and graph features using Databricks Feature Store
* Use Databricks AutoML to create models for predicting telco customer churn
* Take proactive steps to retain telco customers and improve the overall customer experience

Click on the "Get instant access" button in the top right corner to clone the solution accelerator repo into your workspace. Once the repo is cloned into your workspace, please execute the **RUNME** notebook in the repo in order to create the cluster and job you can use to run the notebooks.