Installer data-science-studio avec Homebrew Cask

Liens du projet

• Page d'accueil
• Page du gestionnaire de paquets

Commandes et alias

Aucun alias exécutable n'a été trouvé dans la base locale des paquets.

Historique du projet

Dataiku Data Science Studio, commonly called Dataiku DSS, was developed as a collaborative platform for building and operationalizing data and machine-learning workflows. Its scope grew from data preparation and modeling into automation, application development, deployment, monitoring, governance, and generative-AI workflows.

DSS stores most primary configuration as files and gives each project built-in Git-based version control. Runtime databases retain secondary state such as job and scenario history, metrics, incremental-computation state, discussions, and user-facing activity timelines.

Historique d'adoption

DSS developed into an enterprise platform spanning interactive data preparation, notebooks, visual machine learning, automation, governance, and production operations. Its documentation distinguishes design, automation, API, and governance roles and provides extensive administration guidance for durable deployments.

The macOS application lowered the barrier to local experimentation, while server installations and managed Dataiku offerings address collaborative and production use. Homebrew Cask packages the local macOS launcher rather than the complete range of Dataiku deployment models.

Modes d'utilisation

Analysts and data scientists use DSS through a visual Flow, notebooks, code recipes, machine-learning interfaces, dashboards, and collaborative projects. Administrators operate instances through the documented data directory, command-line utilities, backups, logging, runtime databases, security settings, and monitoring integrations.

Each DSS project is backed by a Git repository, and saved changes can be committed automatically or explicitly. Developers extend and automate the platform with Python and R code, plugins, APIs, code environments, and deployment components.

Pourquoi les passionnés de paquets s'y intéressent

DSS is significant to package enthusiasts because it is simultaneously a desktop-installable product and a server-oriented data platform with its own data directory, embedded runtime databases, command-line administration utilities, code environments, plugins, APIs, and Git-backed project storage.

Its data directory exposes the operational anatomy of the platform: configuration, projects, recipes, notebooks, models, logs, caches, databases, code environments, and histories live under a single installation-selected root that administrators can back up and migrate.

Chronologie

• 2013: Dataiku was founded and began developing its collaborative data-science platform.
• 2020s: DSS expanded across machine learning operations, governance, APIs, applications, and managed-cloud deployment.
• 2026: The reviewed Homebrew cask distributes Data Science Studio 15.0.1 for macOS.

Related projects

• Dataiku Cloud
• Dataiku Govern
• Dataiku API Node
• Jupyter
• Git
• Hadoop
• Spark
• Kubernetes

Sources

• https://developer.dataiku.com/latest/
• https://doc.dataiku.com/dss/latest/
• https://doc.dataiku.com/dss/latest/collaboration/version-control.html
• https://doc.dataiku.com/dss/latest/operations/datadir.html
• https://www.dataiku.com/