Databricks Intelligence Platform for C360: Reducing Customer Churn

The Databricks Data Intelligence Platform is built on a lakehouse to provide an open, unified foundation for all data and governance. In this demo, we’ll show you how to build a customer 360 solution, delivering data and insights that would typically take months of effort on legacy platforms.

This demo covers the end-to-end solution, powered by Databricks:

• Ingest data from external systems (such as Salesforce) with Lakeflow Connect and then transform it using DLT, a declarative ETL framework for building reliable, and maintainable data processing pipelines
• Your ingested data is secure, governed by Unity Catalog
• Leverage Databricks SQL and the warehouse endpoints to build a dashboard to analyze the ingested data and understand the existing churn
• Build a machine learning model with Databricks AutoML to understand and predict future churn
• Orchestrate all these steps with Databricks Workflows

 

To install the demo, get a free Databricks workspace and execute the following two commands in a Python notebook

Dbdemos is a Python library that installs complete Databricks demos in your workspaces. Dbemos will load and start notebooks, DLT pipelines, clusters, Databricks SQL dashboards, and warehouse models … See how to use dbdemos

 

Dbdemos is distributed as a GitHub project.

For more details, please view the GitHub README.md file and follow the documentation.
Dbdemos is provided as is. See the License and Notice for more information.
Databricks does not offer official support for dbdemos and the associated assets.
For any issue, please open a ticket and the demo team will have a look on a best-effort basis.