Build a Data-Powered Organization with KNIME Data Apps

Deploy data science as completely transparent, flexible data apps for technical and business end-users.

Why Data Apps Aren't Getting Deployed 

Much of data science work eventually is served up as browser-based data apps--tooling for end users to understand, explore or perform an action on business critical data. Typically, deploying data apps means a host of engineering work: understanding the staging and dev environments, HTML, CSS, Javascript, HTTP requests, REST APIs, etc.

How Visual Programming Addresses the "Final Mile" Problem

KNIME provides an intuitive drag & drop environment, for both creating and deploying data science.

No coding required (but allowed)

Create data science and deploy using the same intuitive environment, and without ever writing a line of code, unless you want to.

Invoke models & analyses of any level of complexity

Deploy data science of any level of sophistication--whether it’s a simple form accepting data, or it’s a sophisticated ML-powered predictive analysis.

Apply both, data and business expertise

Design data apps that fold in interaction, so you can capture domain expertise of business-line counterparts.

Deploy automatically

Choose to deploy any workflow that is uploaded to KNIME Server automatically. Set permissions to control access to data apps, or make them accessible via a shareable link. Alternatively, embed the data app in a third party application.

Easily explain and replicate your results

Visual programming environments enable swift prototyping and auditing, since every logical step is readable to technical and non-technical stakeholders.

Customize UI for Bespoke Use Cases

Choose your level of complexity and interactivity, for the best user experience.

Build a simple, static report.

Or a dynamic, interactive app.

How KNIME Data Apps Work



  1. Access and blend your data in KNIME’s visual programming environment.

  2. Reach out to any number of technologies integrated in KNIME’s open ecosystem (scripting languages like Python, machine learning libraries like H2O, etc)

  3. Construct your data apps using the same visual, intuitive environment, by dragging and dropping nodes or components onto the page.

  4. Specify permissions. Share your data app through a secure WebPortal or create a shareable, embeddable link.

  5. Share with 5, 10, or 1000 end users.

  6. Monitor and easily tweak based on feedback or new ground truth.

Focus on Data Science, Not HTML

Fill out the form below to connect with our Customer Care team and learn about how KNIME Software can help you deploy data apps to your organization.