![Ravindra N.](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Ravindra N.") RN Ravindra N. SDET - 2 Oil & Energy Enterprise (\> 1000 emp.) 7/18/2026 "Unified, Low-Code Platform That Boosts End-to-End Data & AI Productivity" 4.5/5 What do you like best about Dataiku? What I like most about Dataiku is its ability to bring data preparation, analytics, machine learning, and deployment into a single collaborative platform. It enables both technical and non-technical users to work together, making it easier to build end-to-end data and AI workflows. Visual, low-code interface for building data pipelines and machine learning workflows. Support for Python, SQL, and R, allowing advanced users to customize projects when needed. Strong collaboration features with versioning and project sharing. Seamless integration with databases, cloud platforms, and big data technologies. Built-in tools for model deployment, monitoring, and governance. For me, the most valuable feature is the combination of visual workflows and code-based flexibility. I can quickly prototype data pipelines visually while still using code for advanced transformations or custom machine learning logic. The biggest benefit is improved productivity. Dataiku reduces the time needed to prepare data, develop models, and deploy AI solutions, while enabling better collaboration between data scientists, analysts, and business teams. Review collected by and hosted on G2.com. What do you dislike about Dataiku? The biggest drawback is the complexity of large projects. As workflows grow, managing dependencies, pipelines, and multiple collaborators can become challenging without careful project organization. Complex projects with many datasets and workflows can become difficult to organize and navigate. Some advanced capabilities require a solid understanding of data engineering or machine learning concepts. Review collected by and hosted on G2.com. What problems is Dataiku solving and how is that benefiting you? Dataiku solves the challenge of managing the entire data and machine learning lifecycle in one place. Instead of relying on separate tools for data preparation, model development, deployment, and monitoring, Dataiku provides a unified platform that enables teams to collaborate more efficiently. Simplifies data preparation and transformation through visual workflows. Centralizes analytics, machine learning, and model deployment in a single platform. Enables collaboration between data scientists, analysts, engineers, and business users. Integrates with cloud platforms, databases, and big data ecosystems. Supports governance, version control, and monitoring for production AI models. In my workflow, Dataiku helps accelerate data analysis and machine learning projects by reducing the effort needed to build pipelines and manage data. Its visual interface allows quick prototyping, while the ability to use Python and SQL provides the flexibility needed for more advanced use cases. The biggest benefit is improved efficiency and collaboration. Dataiku reduces the time required to move from raw data to production-ready insights, enabling teams to deliver analytics and AI solutions faster while maintaining better governance and reproducibility. Review collected by and hosted on G2.com. Show More Our network of Icons are G2 members who are recognized for their outstanding contributions and commitment to helping others through their expertise. G2 IconCurrent UserValidated ReviewerIncentivizedSource: G2 invite See what 213 reviewers think of Dataiku 4.4 out of 5 ยท Verified reviews from real users [ Read all reviews ](https://www.g2.com/products/dataiku/reviews)