- Using the internal Python API, a Data Scientist can read a Dataiku DSS dataset into a dataframe, process the dataframe with Python code, and then write back to a Dataiku DSS dataset. Examples include:
Working Within Dataiku (Basics)
Using the internal R API, a Data Scientist can read a Dataiku DSS dataset into a dataframe, process the dataframe with R code, and then write back to a Dataiku DSS dataset. Examples include:
Automating Your Work in Dataiku
A Data Scientist can create custom scenarios using the internal Python API.
An Application Developer can query scoring services on the Dataiku API node.
Bundle and Service Package Deployment
Using the Public API, a Production Environment Manager can:
Administering Dataiku Remotely
Using the Public API, an Administrator can:
- Manage security settings, such as creating users, groups, and projects, on a Dataiku DSS instance
- Manage connections from Dataiku to various data stores
- Populate a project with datasets, recipes, and models according to preset configurations
In this way, you can spin up and take down Dataiku instances as they are needed on cloud infrastructures.