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Tutorials

Discover the power of Lakehouse. Install demos in your workspace to quickly access best practices for data ingestion, governance, security, data science and data warehousing.

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Demos by use case

Access end-to-end demos for a range of use cases — from data ingestion to dashboards to machine learning models.

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One-line installation

With dbdemos, quickly set up the resources you need: data, notebooks, DLT pipelines, workflows, ML and SQL endpoints.

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Product-focused demos

Learn about Databricks products. dbdemos covers it all — Delta Live Tables, streaming, deep learning, MLOps and more.

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Tutorials quickstart

Install demos directly from your Databricks notebooks

Load the dbdemos package in a cell

%pip install dbdemos

List and install any demo

import dbdemos
dbdemos.list_demos()
dbdemos.install('lakehouse-retail-c360')

Explore all tutorials

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Lakehouse for C360: Reducing Customer Churn

Centralize customer data and reduce churn: Ingestion (DLT), BI, Predictive Maintenance (ML), Governance (UC), Orchestration.

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Lakehouse for IoT & Predictive Maintenance

Detect faulty wind turbine: Ingestion (DLT), BI, Predictive Maintenance (ML), Governance (UC), Orchestration.

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Retail Banking - Fraud Detection

Build your Banking platform and detect Fraud in real-time. End 2 End demo, with Model Serving & realtime fraud inference A/B testing.

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Lakehouse - Credit Decisioning

Build your banking data platform and identify credit worthy customers.

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Lakehouse for HLS: Patient Readmission

Build your data platform and personalized health care to reduce readmission risk

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DEMO CENTER

See the full range of Databricks demos

Video demos. Bite-size overviews. Interactive product tours.

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dbdemos is distributed as a GitHub project

For more details, please open the GitHub README.md file and follow the documentation.

dbdemos is provided as is. See the License for more information. Databricks does not offer official support for dbdemos and the associated assets.

For any issue, please open an issue and the Demo team will have a look on a best-effort basis. See the Notice for more information.