Databricks and Dash Integration

Dash can be used as a front-end platform for the Databricks SDK, and in turn, the Jobs API. Run a demand forecasting notebook on Databricks from the comfort of a Dash web application built with Python.

The process for building at-scale interactive Plotly Dash analytics apps for large quantities of industrial IoT time-series data in conjunction with the Databricks SQL Python connector (DB SQL).

Watch the full webinar recording to learn how Ballard solves challenges in operationalizing and scaling end-to-end data collection, analytics, and visualization workflows.

Ballard Power Systems transitioned to Azure cloud-based architecture, leveraging Databricks for data ingress, at-scale analytics, and computing, alongside Dash Enterprise for interactive reporting and visualization.

Dash Enterprise enabled Holmusk to maximize data-driven insights within their NeuroBlu platform, seeing faster development, decision-making, and deployment. They are also adopting Databricks to ensure long-term scalable data and analytics architecture.

With their product, Ascentia, Collins Aerospace helps airlines ensure reliable flight schedules and fewer delays by anticipating aircraft maintenance issues in advance. They use Dash Enterprise and Databricks to develop production-grade, highly-custom, data-rich apps that are not possible with other tools. Watch the presentation.

Dash Enterprise front-end framework and Databricks back-end architecture empower Sidmach to go beyond traditional BI tools. View the webinar highlight reel.

Plotly is pleased to be an early collaborator on the launch of Databricks Lakehouse Apps. Currently, over 3200 enterprises use Plotly & Dash and Databricks, and we are looking forward to what this joint venture will mean for the future of data and AI.

Using Plotly and Dash, Mitzu.io created a purpose-built analytics solution that takes data from an at-scale lakehouse, interpreting complex delta table schema and identifying variations in event properties.

Revenue.ai share how they built an enterprise-grade production data app that seamlessly connects with their enterprise data architecture.

After examining trends across 9,000 global customers, Databricks ranks Plotly second in data and AI products, focusing on production data apps for interactive, at-scale analytics instead of traditional BI.

Maximizing the value of Databricks-enabled Dash apps using new SQLAlchemy integration

Uniper develops trading decision-support tools and advanced analytics data apps using a workflow that includes initial collaboration in Azure Databricks notebooks. View the webinar highlight reel.

Migrating from Excel using Databricks SQLAlchemy & Plotly Dash AG Grid to deliver editable data apps with write-back capabilities

The process for building at-scale interactive Plotly Dash analytics apps for streaming data via Databricks is accomplished by using the Databricks Structured Streaming solution in conjunction with the Databricks SQL python connector (DB SQL). Watch the joint technical webinar.

For building Plotly Dash apps on Databricks, the integration process is identical to any data warehouse. Use the databricks-sql python connector (DBSQL) to create a jdbc/odbc connection to a DBSQL endpoint, or use an ORM such as SQLAlchemy.

Within one year, Dash enabled a major public utility to reduce its customer complaints by 10 times, scaling Dash usage within the company and integrating AI and Databricks.