Databricks has created a new tool called Databricks Apps that makes it easy to build and use internal data and AI applications on AWS and Azure. This tool helps teams work faster and more efficiently with data and AI.
The new feature allows developers to build applications natively within the Databricks environment using popular frameworks like Dash, Shiny, Gradio, Streamlit, and Flask. This innovative solution enables the creation of tailored data applications specifically designed for non-technical users, using code instead of SQL, thereby making complex data insights more accessible within organizations. For instance, marketing teams can utilize Databricks Apps to develop customized dashboards that visualize campaign performance metrics, empowering team members without technical expertise to easily interpret and act on data. The platform also allows developers to integrate AI components, enhancing flexibility by enabling the use of specific AI models for tasks such as sentiment analysis on customer feedback or predictive modeling for sales forecasts.
Once developed, apps are deployed and managed directly in Databricks, eliminating the need for teams to configure and oversee infrastructure. These applications adhere to existing data access controls defined in Unity Catalog, ensuring a unified governance model across the organization.
“We’re excited to launch Databricks Apps and help organizations harness the full potential of their data and AI investments with custom applications that run seamlessly within their Databricks environment,” said Adam Beavis, Vice President & Country Manager for ANZ at Databricks. He noted that while Australian and New Zealand organizations are eager to extract more value from their data, the traditional process of building and deploying internal data applications has been complex and time-consuming. “Databricks Apps addresses these challenges head-on, providing a powerful yet simple experience for building internal data applications,” he added.
Key advantages of Databricks apps
1. Simple to Build:
Databricks Apps allows developers to create applications that operate directly within the Databricks environment or with IDEs like Visual Studio Code and PyCharm. Data scientists and engineers can quickly develop and refine apps using familiar Python frameworks such as Dash, Gradio, and Streamlit. Pre-built Python templates further expedite the app-building process.
2. Production-Ready and Automated Deployment:
Developers benefit from automatically provisioned serverless compute, eliminating the need for additional infrastructure. Databricks Apps supports industry-leading development practices, offering seamless integration with workflows and support for Git version control and CI/CD pipelines.
3. Built-in Governance:
Databricks Apps ensures that data remains secure within the Databricks environment unless users opt to share it. Each app features robust security measures, including granular access control and automated user authentication using OIDC/OAuth 2.0 and SSO. Additionally, Unity Catalog’s lineage capabilities enhance data traceability and compliance.
Databricks Apps can facilitate the development of a variety of internal applications, including:
Custom Data Visualizations: Dynamic, data-driven visualizations for real-time exploration and analysis.
AI Applications: Apps leveraging machine learning models for predictive maintenance, customer segmentation, or fraud detection.
Self-Service Analytics: User-friendly interfaces enabling business users to conduct complex analyses.
Data Quality Monitors: Custom tools for tracking and improving data quality.
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Databricks has introduced Databricks Apps, enabling developers to build user-friendly applications directly within its platform News, Databricks Dynamic Business
