Quick Verdict
Dataiku is an end-to-end data science and machine learning platform that enables teams to build, deploy, and manage AI projects collaboratively. From data preparation to MLOps, it bridges the gap between data scientists, analysts, and business users with visual workflows and code-based development.
Best for: Enterprise data science teams, Organizations scaling ML operations, Companies needing governed AI, Mixed technical/non-technical teams
Dataiku
Dataiku is an end-to-end data science and machine learning platform that enables teams to build, deploy, and manage AI projects collaboratively. From data preparation to MLOps, it bridges the gap between data scientists, analysts, and business users with visual workflows and code-based development.
Best for: Enterprise data science teams • Organizations scaling ML operations • Companies needing governed AI • Mixed technical/non-technical teams
Key Features
- Visual ML workflow builder
- AutoML for rapid model development
- MLOps and model monitoring
- Collaborative notebooks (Python, R, SQL)
- 300+ data connectors
- Responsible AI toolkit
- Feature store
- Model deployment automation
Pros
- Excellent collaboration features
- Supports both visual and code-based work
- Strong MLOps capabilities
- Comprehensive governance tools
- Active community and marketplace
Cons
- Expensive enterprise pricing
- Resource-intensive platform
- Can be overwhelming for beginners
- Some features require coding
Pricing
| Plan | Details |
|---|---|
| Starter | ~$4K/mo |
| Enterprise | Custom |
Full MLOps platform
Tips & Best Practices
Use reusable project templates with standard lifecycle: data quality checks, evaluation, bias tests, approval workflows
Leverage pushdown architecture (SQL, Spark, Kubernetes) so heavy processing runs where data already lives
Define explicit promotion workflows with Dataiku Govern: who can approve, what evidence needed, when to review
Set up built-in monitoring for data drift, model performance, and service health with alerts to right owners
Add data quality rules directly into Flows so broken inputs block downstream steps automatically
Use scenarios as orchestration backbone for data refresh, training pipelines, batch scoring, and reporting
Treat GenAI same as ML: register, version, test with guardrails (toxicity, PII), monitor, and govern
Features
- Visual ML workflow builder
- AutoML for rapid model development
- MLOps and model monitoring
- Collaborative notebooks (Python, R, SQL)
- 300+ data connectors
- Responsible AI toolkit
- Feature store
- Model deployment automation
Best for: Enterprise data science teams • Organizations scaling ML operations • Companies needing governed AI • Mixed technical/non-technical teams
Pros
- Excellent collaboration features
- Supports both visual and code-based work
- Strong MLOps capabilities
- Comprehensive governance tools
- Active community and marketplace
Cons
- Expensive enterprise pricing
- Resource-intensive platform
- Can be overwhelming for beginners
- Some features require coding
Final Recommendation
Dataiku is a paid AI tool best suited for Enterprise data science teams and Organizations scaling ML operations.