Data and AI projects require teamwork across multiple roles, from technical, hands-on builders to business users. But too often, teams work in silos, using disconnected tools that slow progress. Dataiku eliminates these barriers by creating a shared space where technical and non-technical users collaborate efficiently, ensuring AI projects move forward faster and with greater impact.
A Visual Flow for Clear Collaboration
Effective collaboration starts with clarity. The Dataiku Flow provides a visual representation of data pipelines, acting as both a workspace and a communication tool.
- Consistent visual language and common objects make workflows easy to follow.
- Context tags, annotations, and flow zones help teams structure and organize work.
- A centralized workspace keeps all changes, decisions, and project knowledge in one place.
With workflows that are both transparent and structured, onboarding new team members becomes seamless, and teams stay aligned as projects evolve.
Coders and Non-Coders in One Platform
Dataiku brings coders and non-coders together in a shared environment, ensuring that everyone can contribute seamlessly to AI projects.
- Non-coders can use point-and-click tools for data preparation, analysis, and reporting.
- Coders can write Python, R, SQL, or other languages, seamlessly integrating their work into the Dataiku Flow.
- Because every piece of custom code is documented like visual elements, technical and non-technical users can collaborate without friction, eliminating bottlenecks in the workflow.
By breaking down silos and fostering real-time collaboration, Dataiku helps teams work more efficiently. For example, OVH saw a 40% improvement in how quickly their data scientists complete projects, thanks to faster data access, streamlined preparation, workflow monitoring, and stronger cross-team collaboration. Aviva’s data science team achieved a 5x increase in efficiency by streamlining the entire data project lifecycle — from model development to production — through stronger collaboration.
With a platform designed for seamless collaboration, Dataiku removes friction from AI development, empowering teams to scale their efforts and drive meaningful business impact.
Reusing Work to Accelerate AI Initiatives
Starting from scratch slows teams down. Dataiku makes it easy to find and reuse past work so teams can build on existing efforts rather than duplicating them.
- Central hubs — such as the catalog, feature store, home page, and plugin store — allow teams to easily discover existing projects and datasets.
- Copy/paste functionality for subflows and recipes enables users to quickly incorporate proven workflows into new projects.
By streamlining knowledge sharing and reuse, Dataiku helps teams deliver AI-driven insights faster.
Scaling Expertise With Packaged Assets
Teams can package subflows and Python scripts into reusable recipes or plugins, making advanced analytics accessible to business users.
- Coders can create and share pre-written code snippets (including Git imports) to maintain consistency across projects.
- Business users can leverage these tools through an easy-to-use visual interface, eliminating reliance on technical teams for routine tasks.
This approach scales expertise across the organization, enabling more people to contribute without requiring deep technical knowledge.
Keeping Knowledge in One Place, With Built-In Documentation
AI projects require continuity, especially as teams grow and evolve. Dataiku centralizes project knowledge and collaboration tools to ensure alignment:
- Project wikis provide a structured space to document decisions, methodologies, and workflows.
- Integrated chat, to-do lists, and discussion threads keep conversations within the project — no more scattered notes across different tools.
By embedding documentation and discussions directly into the platform, Dataiku ensures that institutional knowledge is preserved and accessible at all times.
Automating Documentation for Compliance & Transparency
Regulatory compliance and AI governance require thorough documentation, but maintaining records manually is time-consuming. Dataiku automates flow and model documentation, allowing teams to stay compliant with minimal effort.
- Customizable templates generate metadata and visualizations that snapshot project progress.
- Automated scheduling keeps documentation up to date, removing the need for manual updates.
With structured, real-time documentation, teams can focus on execution while maintaining full transparency and compliance.
Work Smarter With Dataiku
True collaboration goes beyond using the same tool — it means ensuring teams stay aligned, workflows remain clear, and work is reusable and scalable. With a unified workspace, seamless code integration, reusable assets, built-in documentation, and automated reporting, Dataiku makes AI collaboration effortless.