| Senior Data Scientist at Deloitte | 4.5 | I primarily use Dataiku for life sciences data pipelines, finding its visual recipes and automation invaluable. It significantly cut project delivery time by 40% and AWS costs by 70%. While documentation needs improvement, I highly recommend Dataiku for its efficiency. |
| Cdao/Global Head Of Data And Analytics at Givaudan Roure | 4.0 | I find Dataiku a valuable all-in-one platform for data science, accelerating model building and collaboration. Despite a challenging setup and high pricing, its stability and integrated features offer significant ROI, though I'd like more advanced NLP capabilities. |
| Solution Architect at a pharma/biotech company with 10,001+ employees | 4.0 | I find Dataiku highly effective for ETL, ML, and automation, significantly boosting team productivity and enabling non-coders. While data analysis is a strong point, I believe dashboards and API integration could improve, and customer support sometimes lags. |
| Head of Delivery & Practice (Data & AI) at a recruiting/HR firm with 201-500 employees | 4.5 | I find Dataiku a complete, easy-to-use platform for AI/ML/GenAI projects, valuing its high ROI, collaboration features, and stability. While powerful and scalable, I wish its complex pricing could be simplified. |
| Data Scientist at Ericsson | 4.0 | I use Dataiku for robust data pipelines, quality, and AutoML, appreciating its flexible integration and clickable interface. Despite being stable, its high cost limits team collaboration, making ROI hard to measure. I rate it 8/10. |
| Data Analyst | 4.5 | I highly value Dataiku's reusable recipes for data preparation, which significantly automate and save time on repetitive tasks. It's an intuitive, scalable platform enabling end-to-end projects. Though nearly perfect, the interface could be better organized. It’s the best solution. |
| Manager at a tech vendor with 10,001+ employees | 3.5 | I use Dataiku for demand forecasting, valuing its flow overview and low-code nodes, especially for non-technical users. However, I find its visualization features, integration, stability, and scalability need improvement. I'd rate it 7/10. |
| Data Science Lead at a mining and metals company with 10,001+ employees | 4.0 | We use Dataiku for oil and gas exploration, valuing its visual workflow and positive ROI. Good support, but we need better parallel machine learning capabilities and integration, rating it eight out of ten. |
