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Dataiku

Dataiku

Enterprise AI + data science platform.

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Monthly visits
1.5M
Growth
+6.0%
Rating
4.1 (35)

About Dataiku

Dataiku is an enterprise-grade platform that combines data preparation, machine learning, and AI deployment into a single collaborative environment. It allows data scientists, analysts, and business users to work together on the same projects, moving data from raw ingestion through transformation, model training, and production deployment without switching between disconnected tools. The platform supports both visual, low-code workflows and full code-based development in Python, R, and SQL, making it accessible to users across different technical skill levels. Built-in AI assistants help with tasks like generating code, explaining datasets, and accelerating model development. Primary use cases include building and operationalizing machine learning models, automating data pipelines, running large-scale analytics, and governing AI projects across an organization. Teams use Dataiku for customer churn prediction, fraud detection, demand forecasting, risk modeling, and a range of other applied ML scenarios. The platform integrates with major cloud providers including AWS, Google Cloud, and Azure, as well as data warehouses like Snowflake and Databricks. It also includes tools for model monitoring, explainability, and compliance, which are increasingly important for organizations operating under regulatory scrutiny. A project hub and centralized governance layer allow larger organizations to manage who builds what and how models are deployed at scale. Dataiku is aimed squarely at mid-size to large enterprises that need to standardize and scale their data and AI work across multiple teams and departments. It is not a lightweight or entry-level tool. Pricing is not publicly listed on the website and is based on enterprise contracts, typically negotiated based on the number of users, deployment model, and required features. A free tier called Dataiku Free Edition is available for individual users and small teams, offering a limited but functional version of the platform suitable for learning and small-scale projects.

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