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Backed By Dataiku
Centralized AI platform for collaborative data science and Everyday AI.
Dataiku is a centralized AI platform designed to unite people, data, and technology, enabling organizations to build, deploy, and manage data science projects at scale. It provides a collaborative environment for data scientists, data engineers, and business users.
Enable data scientists, engineers, and business users to work together.
Foster innovation through a centralized platform.
Manage data science projects from development to deployment.
Scale AI initiatives across the organization.
Utilize Dataiku’s platform for rapid AI development.
Integrate AI into business processes.
Unite people, data, and technology for improved data access.
Streamline data workflows.
Install on your infrastructure (Mac, Linux, VM)
Fully managed by Dataiku (SaaS)
Enterprise-wide collaboration
Visual Data Preparation and Wrangling (No-Code/Low-Code)
Automated Machine Learning (AutoML)
Code-First Development (Python, R, SQL, Jupyter Notebooks)
Collaborative Project Management and Version Control
Data and Feature Store
Real user experiences from across different platforms
I really appreciate how the graphical user interface handles paths and threads. It allows you to manage all your code and datasets visually, and everything is automatically aligned, which makes the experience very soothing to use. The collaboration features facilitate great teamwork.
Verified User
N/A
to scale AI/ML and GenAI across multiple teams and use cases.
ts, engineers, analysts, business users) requiring a platform that supports no-code to full-code collaboration.
dget (due to high enterprise pricing).
only tool (Tableau or Power BI alternatives would be cheaper).
Democratizing AI (Everyday AI) by providing a unified, collaborative, and governed platform that empowers all team members—from data scientists to business analysts—to build, deploy, and manage high-impact AI/ML and Generative AI projects at enterprise scale.
High pricing makes it less accessible for small organizations and individual users (outside of Free Edition/Trial). Steep learning curve for accessing and utilizing advanced functionality. Can be resource-intensive, requiring robust infrastructure (especially for self-hosted versions). Limited documentation available for certain advanced features/APIs (user-reported complaint). Chart styling is not as intuitive as expected (user-reported complaint).