Dataiku Data Science Studio is acclaimed for its versatile capabilities in advanced analytics, data preparation, machine learning, and visualization. It streamlines complex data tasks with an intuitive visual interface, supports multiple languages like Python, R, SQL, and scales efficiently for large dataset handling, boosting organizational efficiency and collaboration.
| Product | Market Share (%) |
|---|---|
| Dataiku | 11.7% |
| Databricks | 13.9% |
| KNIME Business Hub | 11.9% |
| Other | 62.5% |
| Title | Rating | Mindshare | Recommending | |
|---|---|---|---|---|
| Databricks | 4.1 | 13.9% | 96% | 91 interviewsAdd to research |
| KNIME Business Hub | 4.1 | 11.9% | 94% | 60 interviewsAdd to research |
Users highlighted that the platform's ability to streamline data science processes and enhance collaboration among team members leads to more efficient project completion. Dataiku's versatility and user-friendly interface enable users to manage large datasets effectively and apply complex algorithms, which in turn results in significant time savings and increased productivity. Additionally, the software's scalability allows for ongoing growth and adaptation in diverse environments.
| Company Size | Count |
|---|---|
| Small Business | 4 |
| Midsize Enterprise | 1 |
| Large Enterprise | 7 |
| Company Size | Count |
|---|---|
| Small Business | 276 |
| Midsize Enterprise | 154 |
| Large Enterprise | 909 |
Dataiku was previously known as Dataiku DSS.
BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
| Author info | Rating | Review Summary |
|---|---|---|
| Data Science Lead at a mining and metals company with 10,001+ employees | 4.0 | We use Dataiku for oil and gas exploration because of its efficient workflow capabilities and visual interface, making tasks easier without needing a data scientist. Although there are integration issues, the ROI seems positive compared to alternatives considered. |
| Manager at CTTI - Centre de Telecomunicacions i Tecnologies de la Informació | 4.0 | I use Dataiku primarily for preparing health investment research cohorts, valuing its traceability and collaboration features. With multiple engineers on my team, integration with machine learning is crucial. However, the licensing cost is high, and I seek more healthcare sector experience. |
| Big Data Consultant at a computer software company with 1,001-5,000 employees | 4.0 | My company sells licenses for Dataiku and Alteryx, and I've seen its drag-and-drop and automation features significantly enhance clients' machine learning model development. However, more flexibility with code-based features would be beneficial. |
| Cognitive Business Operation at a consultancy with 10,001+ employees | 5.0 | I primarily use Dataiku for data science and AI applications. It's a leader in capabilities and integration but is expensive with limited support. Lower pricing would enhance ROI. Alternatives include Converge.io, Domino Data Lab, and ClearML. |
| Data Scientist at Ericsson | 4.0 | I've used Dataiku for four years to manage data pipelines effectively; it's powerful and flexible but expensive, making collaboration limited. Its AutoML features are helpful, though ROI is unclear due to shared tools and unclear monetization tracking. |
| Data Scientist at Electricite De France | 3.5 | I use Dataiku for data science and machine learning, enjoying its recipe features for easy data preparation without coding. However, integration with GitHub is challenging, and it struggles with complex data types like text and image. |
| Consultant at Netsoft | 4.0 | My current client uses Dataiku for sentiment analysis and large language models, mainly in marketing and analytics. While it offers strong feature selection, more coding is required compared to DataRobot, which is more suited for financial tasks. |
| Senior Data Engineer at One Point | 5.0 | No summary available |
