Getting Started

Entirely new here?

Understand the Value Proposition of Dataiku DSS.

Dataiku Data Science Studio Concepts

First time using Dataiku DSS?

The Lab and the Flow

Draft work in the Lab

When beginning a data project, you should start by drafting your work in the Lab environment

  • the Visual Analysis tool lets you draft data preparation steps, create charts, and build machine learning models

  • the code notebooks let you explore your data interactively.

Build Data Pipelines in the Flow

The Flow is an end-to-end visualization of your data preparation steps from source to final data products.

Sampled vs. Complete Data

When working on a prepare recipe or in an analysis, you get live visual feedback for all the preparation steps that you add. This couldn’t happen if you were previewing whole datasets (big data just doesn’t fit in DSS’s memory), so you are simply looking at a sample.

Keeping Everything Up-to-date in the Flow

Rebuilding Datasets

When you edit an existing recipe or when your data is updated, you will need to rebuild your downstream datasets to update their contents.

Deploy Flows in Production

Dataiku DSS greatly facilitates all automation and monitoring tasks, so make sure you understand all production features related to Flow automation.

Collaboration

Dataiku DSS is all about making teams more efficient, so don’t forget to promote your work to others!