What you can do with Dataiku
Every task in plain language. Pick one, and we can help you get access.
18 things you can do
Dataiku
Dataiku provides an enterprise AI and analytics platform that empowers data teams to collaboratively prepare data, build predictive models, and deploy AI-driven applications at scale. The platform integrates data engineering, machine learning, and operationalization tools, offering a unified environment for data scientists, analysts, and business users to turn data into actionable insights. It sup
18 multi-step recipesRecipes: multi-step jobs
Audit Recipe and Project JobsInspect a recipe and review the project's jobs.Bootstrap Project with First Dataset
Create a project and seed it with a first dataset.Browse Managed Folder Contents
List managed folders and read one folder's contents.Build Dataset and Poll Job
Start a dataset build job and poll it to a terminal state.Create Dataset, Set Schema, and Build
Create a dataset, set its schema, and start a build.Create Govern Artifact with Custom Fields
Create an artifact, set custom fields, and confirm them.Create Govern Blueprint and Version
Create a blueprint, add a version, and confirm the version.Export Project Bundle
Create a project export bundle and confirm it in the bundle list.Import and Preload API Node Generation
Import a generation bundle, preload it, and switch the service to it.Inspect Saved Model
Discover saved models in a project and read one model's details.Inspect and Read a Dataset
Discover a dataset and read a sample of its rows.Promote API Node Generation
Switch a service to a new generation and enable it.Provision DSS User
Create a DSS user, confirm it, and assign groups.Resolve Connection and Run SQL Query
Confirm a connection and execute a SQL query against it.Review Artifact Sign-Off
Add an approve or reject review to an artifact sign-off step.Run Scenario and Poll to Completion
Run a scenario and poll its status until the run finishes.Tag Project Metadata
Update a project's metadata label, description, and tags.Teardown Project
Delete a dataset and then delete the project.