The ability to model and analyze data isn't just the domain of developers and data engineers—it's a vital competency across all facets of a business. At Cube, we've always prided ourselves on delivering a top-notch developer experience, offering a powerful code-first approach that enables developers to craft intricate and efficient data models.

But we also recognize that not everyone is proficient in code, and the opportunity to involve more people in the data modeling process will only strengthen collaboration across data teams and the value you receive from your data. That's why we're thrilled to announce Cube Visual Modeler. This addition to Cube Cloud opens the door for non-technical users to actively participate in data modeling without writing a single line of code, and code-proficient engineers have the option of working in code or no-code.

Bridging the Gap Between Technical and Non-Technical Users

Until now, contributing to data models in Cube Cloud required a solid understanding of code—a barrier that limited participation to those with a technical background. While our code-first approach provides developers with the flexibility and control they need, it inadvertently leaves out valuable contributors who could offer critical business input.

We've listened to your feedback and understand that collaboration is key. Many of our customers have expressed the need for a visual interface that allows data analysts and business users to contribute directly to data models. With Cube Visual Modeler, we're making that a reality.

Using Canvas as a Visual Interface for Interactive Data Modeling

At the heart of Cube Visual Modeler is the canvas-style interface. Think of it as a shared workspace where you can visualize, create, and modify data models in an intuitive and user-friendly environment. Replacing Data Graph, Canvas will be one place to see and edit data models visually.

Canvas displays your current data models, allowing you to see how different elements connect and interact. This visual representation makes it easier for non-technical users to understand the structure without sorting through code.

Users can build new cubes and views from scratch directly within Canvas. This feature empowers teams to expand their data models collaboratively, bringing diverse perspectives to the table. Modify joins, measures, and dimensions with simple form-based actions.

Every change made in Cube Visual Modeler is translated into code behind the scenes. This approach maintains the integrity and flexibility of Cube's code-first philosophy while expanding accessibility.

  • Code Generation: As users make changes on Canvas, the system automatically generates the corresponding code. There's no need to worry about syntax errors or code structure—the interface handles it all.
  • Approval Workflow: Generated code isn't applied immediately. Instead, it goes through your existing code review processes, where data engineers can review, provide feedback, and approve changes via pull requests.
  • Consistency and Control: This method ensures that all contributions, whether from code or no-code users, adhere to the same standards and practices, maintaining a cohesive and reliable data model.

Helping Data Teams Work More Efficiently Together

Cube Cloud now provides you with a choice between the original code-first approach and Cube Visual Modeler, so that modeling becomes more collaborative. Diverse perspectives lead to more comprehensive data models, ultimately driving better business decisions. With more hands on deck, data models can be developed and refined more quickly. Non-technical users no longer rely solely on developers to implement changes, streamlining workflows.

Here's how it benefits non-developers:

  • Ease of Use: Eliminate the learning curve associated with coding. Users can engage with data models intuitively, focusing on their expertise rather than syntax and code structures.
  • Streamlined Workflow: Stop switching between different tools or interfaces. Everything—from viewing to editing—is accessible within Canvas.
  • Enhanced Collaboration: Bring data teams together Business users can contribute their logic directly, leading to more useful and applicable data models.

Cube Visual Modeler also offers significant advantages for data engineers and developers:

  • Insightful Visualization: Assess how well-used an object is before making changes. This visibility helps prioritize efforts and understand the impact of modifications.
  • Seamless Transition Between Code and Visuals: Locate objects within Canvas for context and then switch back to the code for deeper technical work.
  • Controlled Contributions: Review and approve generated code via pull requests. This means data engineers maintain control, ensuring that all updates meet your organization's data modeling standards.

Join the Visual Revolution

At Cube, our mission is to make data accessible and actionable for everyone. The introduction of Cube Visual Modeler is a significant step toward that goal. By empowering a broader range of team members to participate in data modeling, you're fostering a more inclusive and innovative environment.

We remain committed to providing tools that are both powerful and user-friendly, catering to the diverse needs of modern organizations. We can't wait to see how you'll leverage this new capability to drive innovation and success within your teams. Contact Sales to learn more.