A comprehensive technical handbook covering Dataiku Data Science Studio (DSS) — from project setup, data preparation, and visual recipes to machine learning, deployment, governance, and API integration. Designed for data engineers, data scientists, and platform administrators.
Chapters
Environment Setup and User Management
20 min read
Project Lifecycle and Flow Foundations
15 min read
Data Connectivity and Dataset Creation
25 min read
Visual Data Preparation Recipes
25 min read
Advanced Data Wrangling and Join Strategies
20 min read
Window Functions and Time-Series Analysis
20 min read
Python and R Integration in DSS
25 min read
Working with SQL Recipes and Code Environments
20 min read
AutoML: Building Machine Learning Pipelines
25 min read
Feature Engineering and Selection Techniques
20 min read
Model Evaluation and Interpretation
25 min read
Deployment Patterns: API Nodes and Automation
25 min read
Scenarios, Triggers, and Workflow Orchestration
20 min read
Building Interactive Data Apps and Dashboards
20 min read
Governance, Permissions, and Project Security
15 min read
Monitoring and Auditing Model Performance
20 min read
Scaling Dataiku: Clusters and Distributed Computing
25 min read
Best Practices for Collaborative Data Science
15 min read
Career Roadmap and Advanced Certification Path
10 min read