Reference | Navigation bar

The Navigation bar is key to moving between different areas of Dataiku, such as the Flow, machine learning models, notebooks, and dashboards.

You can find the Navigation bar at the top of the screen in a project. It includes several menu icons, starting with the Flow icon.

In many of these menu options, you’ll find a list of elements in your project and options to create new objects. Read on to learn the options in each menu!

Caution

The options available in your menus may vary depending on the version and features used on your Dataiku instance.

Flow menu

The first menu, the Flow menu, is used to return to the Flow from other screens within the project, or to see lists of datasets and recipes used in the Flow. Options include:

Menu	Destination
Flow	The Flow (visual overview) of the project. From the Flow, you can then navigate to any recipe, dataset, model, or other component of the project.
Datasets	List of datasets in the project.
Recipes	List of recipes in the project.
Labeling tasks	List of labeling tasks in the project. Labeling tasks are created and managed through the Labeling visual recipe.
Streaming Endpoints	List of endpoints that handle continuously streaming data.

Visual Analyses menu

The Visual Analyses menu is where you’ll find machine learning models and other tools used to evaluate and compare them. Options in this menu include:

Menu	Destination
Visual Analyses	List of machine learning models or interactive data preparation created in the Lab.
Saved Models	List of models that have been deployed from the Lab to the Flow.
Prompt Studios	Visual interface that allows you to work with large language model (LLM) prompts.
Model Evaluation Stores	Space to collect evaluations of different models that can be used for drift analyses.
Model Comparisons	Space to visually compare the performance of models from multiple evaluations.
Experiment Tracking	Space to store and compare code-based machine learning models. For more information, see the reference documentation on experiment tracking.

Notebooks menu

The Notebooks menu takes you to code-related spaces in Dataiku. Options include:

Menu	Destination
Notebooks	List of all your notebooks, which are interactive coding environments to interact with or manipulate data using a coding language such as Python, R, or SQL.
Webapps	List of your webapps, which are custom applications hosted by Dataiku and used for advanced visualizations or custom frontends.
R Markdown Reports	List of generated documents from a mixture of Markdown and code. For more information, see the Concept | R Markdown reports article.
Libraries	The Library Editor, where you can create your own libraries or helpers and share then within the project for use in Python or R recipes and notebooks.
Code Studios	List of Code Studios, where you can edit code elements in Dataiku with your favorite integrated development environment (IDE), such as JupyterLab or RStudio.

Jobs menu

The Jobs menu helps you monitor automation in Dataiku. Options include:

Menu	Destination
Jobs	List of jobs, or activities happening in the Flow, such as running recipes or executing code.
Scenarios	List of scenarios, or automated tasks such as building datasets or training models.
Automation Monitoring	Space to monitor scenario runs via a daily summary or timeline.

Wiki menu

The Wiki menu takes you to a space where you can create and edit documentation for your project.

Menu	Destination
Wiki	List of articles to document your project.

Dashboards menu

The Dashboards menu navigates to visual reporting tools that help you collaborate and communicate insights about your project.

Menu	Destination
Dashboards	List of dashboards, which are tools to publish elements such as tables, charts, and model reports.
Insights	List of elements that you can add to dashboards.

More options

The More options menu (the three dots to the right of the Dashboards menu) navigates to areas to deploy your models and control other project-level settings.

Menu	Destination
API Designer	API services, which allow you to deploy machine learning models for real-time scoring.
Variables	Space to create global or local variables, which can be used in visual or code recipes, scenarios,and applications.
Bundles	List of bundles, or versioned snapshots of your project.
Macros	Space to create one-shot actions to maintain your project.
Version control	List of commits on your project. For more information, see the reference documentation on version control.
Application Designer	Options to convert your project into a visual application or an application-as-recipe.
Settings	Controls for project-level settings, such as project tags, integrations, automation, engines, and connections.
Security	Project-level security options, including permissions, API keys, and shared objects.