macOS
Homebrew Caskverified · 100%
brew install --cask data-science-studiolocal Homebrew cask metadata
cask
Install data-science-studio with Homebrew Cask
Quick experimentation and operationalization for machine learning at scale. Version 15.0.1 via Homebrew Cask; verified from local package data.
install
Additional install commands
overview
Package summary
Quick experimentation and operationalization for machine learning at scale
Project links
Commands and aliases
No executable aliases were found in the local package database.
history
Project history and usage
Dataiku Data Science Studio is a collaborative data and machine-learning platform for preparing data, building models and applications, automating workflows, and moving projects into production. The Homebrew cask installs its macOS desktop distribution.
Project history
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.
Adoption history
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.
How it is used
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.
Why package nerds care
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.
Timeline
- 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
security posture
No protected-tool coverage found yet
No matching local secret-handling manifest was found for data-science-studio. Package metadata is still published here so future coverage has a stable package URL.
Install behavior
- No Homebrew post-install hook is recorded in formula metadata.
- No Homebrew bottle metadata was recorded.
Recommended review
Before unattended agent use, check whether the tool reads plaintext credentials, writes remote state, publishes artifacts, or shells out to plugins.
local files
Configuration and credential file locations
These source-backed paths show where this package keeps local settings or durable credentials. Automic Vault can use them as review targets for secret scanning, migration, and command approval.
Configuration files
Config paths the tool may read or write during local use.
- Linux
$DSS_DATADIR/config- macOS
~/Library/DataScienceStudio/dss_home/config
Credential files
Credential-bearing paths to review before unattended agent runs.
- Linux
$DSS_DATADIR/config- macOS
~/Library/DataScienceStudio/dss_home/config
executables
Installed executables
| Command | Kind | Exposure | Note |
|---|---|---|---|
| No executable data was present. | |||
freshness
Version and freshness
These signals separate page generation age, package-manager activity, and upstream release comparison. Version lag is warned only when an evidence URL and comparable versions are present.
page generated2026-11-04
manager version15.0.1
manager updated
local dataok
upstreamnot checked
latest detectednot detected
- infoNo package-manager update timestamp was available.low confidence
- infoRelease/tag comparison is only available for GitHub repositories.https://www.dataiku.com/none confidence
install metadata
Package metadata
| Package key | cask:data-science-studio |
|---|---|
| Version | 15.0.1 |
| Package manager | Homebrew Cask |
| Package manager page | https://formulae.brew.sh/cask/data-science-studio |
| Homepage | https://www.dataiku.com/ |
| Upstream docs | https://www.dataiku.com/ |
| Source archive | https://cdn.downloads.dataiku.com/public/launcher/macos/DataScienceStudio-15.0.1-arm64-mac.zip |
| SHA-256 | db79190f424b991af11749c5a17f4f53cc2d005bdc596e9ca315edf58261b1f2 |
| Bottle | not recorded |
| Homebrew post-install | not defined |
| Service | none declared |
registry facts
Source database details
| Source Database | Homebrew cask API |
|---|---|
| Tap | homebrew/cask |
| Full Token | data-science-studio |
| Names |
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| Depends On | |
| Artifacts | |
| Deprecated | no |
| Disabled | no |
source trail
Generated from repository data
This page is generated by av-web from the private package SQLite artifact built by scripts/generate-pkg-sqlite.py.
Combined YAML source
View the package source record on GitHub.
Used sources
- cross-ecosystem install command graph
- curated configuration and credential file locations
- curated package history
- package relationship graph
- package version freshness
- package-page enrichment