# Data & AI Platform (Dataiku)

[Dataiku](https://www.dataiku.com/) is a collaborative platform designed to help teams build, deploy, and manage data pipelines, analytics, and AI/ML models. It brings data engineers, analysts, and data scientists together in one environment, enabling end-to-end work from raw data to production-ready applications.

### Dataiku at UNESCO

At UNESCO, Dataiku is deployed in two separate environments: **Development (Dev)** and **Production (Prod)**. The **Dev instance** is where users explore data, prototype workflows, build and test models, and experiment freely. The **Prod instance** hosts stable, validated projects and automated pipelines that are used operationally. This separation ensures reliability, security, and proper governance of data and analytics activities.

Access the Development Instance: [Dataiku](https://dss-61c005b5-f304e2f4-dku.eu-west-3.app.dataiku.io/home/)

#### User Roles at UNESCO

Access to Dataiku is based on several user levels, each designed to match specific responsibilities and skills:

<table><thead><tr><th width="160">Profile</th><th>Responsabilities</th></tr></thead><tbody><tr><td><strong>Reader</strong></td><td><p></p><p>Can view projects, dashboards, and datasets.</p><p><em>Ideal for staff who need visibility into analytics outputs but do not build or modify workflows.</em></p></td></tr><tr><td><strong>Advanced Analytics User</strong></td><td><p></p><p>Can explore datasets, perform visual analysis, and build basic visual recipes.</p><p><em>Suitable for analysts who work mostly through the visual interface.</em></p></td></tr><tr><td><strong>Data Designer</strong></td><td><p></p><p>Can create datasets, design data pipelines, and manage connections.</p><p>Able to use more advanced visual recipes and some coding features.</p><p><em>Intended for users building reusable data flows.</em></p></td></tr><tr><td><strong>Full Designer</strong></td><td><p></p><p>Full access to code (Python, R, SQL), advanced recipes, plugins, and automation features.</p><p>Can build, deploy, and maintain complex data pipelines or machine learning models.</p><p><em>Suitable for data engineers and data scientists.</em></p></td></tr></tbody></table>

**More Details:** [Dataiku User Profiles](https://doc.dataiku.com/dss/latest/security/user-profiles.html)

#### Requesting Access

To request access to the UNESCO Dataiku instance or to upgrade your user level, please contact the [**data.ai@unesco.org**](mailto:data.ai@unesco.org) team.\
Include your name, unit/section, reason for access, and the role you require.

#### Best practises

* **Use the Dev environment first:** Build and test everything in Dev before requesting deployment to Prod.
* **Document your work:** Add project descriptions, flow zones, and annotations to make your work understandable to others. Complete the wiki in your Dataiku project.
* **Organize your flows:** Avoid unnecessary duplication of datasets or recipes; reuse where possible.
* **Data Quality:** Make sure to follow the [UNESCO Data Quality Standards and Guidelines](https://unesco.gitbook.io/unesco-data-ai/~/revisions/K63ycNbLcgt3qkocHh4Q/good-practices/unesco-data-quality-standards-and-guidelines)

### Learning Ressources

#### Dataiku official documentation

The official Dataiku documentation provides detailed guidance on all features of the platform, including data preparation, machine learning, administration, and best practices. It is the primary reference for understanding how each component of Dataiku works.

Link to the documentation: [doc.dataiku.com](https://doc.dataiku.com/dss/latest/)

#### Dataiku Academy

Dataiku Academy offers free, self-paced online courses and certifications for all skill levels - from beginner tutorials to advanced machine learning and MLOps content. It is the best place to learn how to use Dataiku hands-on through guided exercises.

Access [Dataiku Academy](https://academy.dataiku.com/)


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