Welcome to b-data

Data Science Services and Infrastructure


About b-data

b-data is a company specialised in Data Science services on GPU accelerated computing infrastructure.
Take advantage of our more than 15 years of experience to make your Data Science project a success!

Take a look at Olivier’s skills and professional experience on benz0li.b-data.io.


Open-source software

As advocates of OSS, we sponsor the QGIS project, the Julia language, the R Foundation and the FreeBSD Foundation.


We devote about 20% of our time to OSS and maintain

dev containers,
docker images and
deployment templates

for Data Scientists, ML/AI Engineers, and the like 🧑‍💻.

Furthermore, we provide Data Science Dev Containers for use with VS Code and GitHub Codespaces.
🎯 A unified IDE for the common Data Science programming languages R, Python, Julia and Mojo.
🔥 Most images are also available in a GPU accelerated (nvidia/cuda-based) version.

You can find all this for free on GitHub and GitLab!

Screenshot


Besides, see Olivier’s (benz0li’s) work on GHC musl – Unofficial binary distributions of GHC on Alpine Linux.
ℹ️ The docker image used to build the statically linked Linux binary releases of Pandoc.


Data Science

We are interested in your specific use case, wherefore we offer a lean and tailor-made solution.
For a general introduction to Data Science, we recommend DataCamp.


R expertise
Databases with R (DBI, odbc)
Data Exploration (tidyverse)
Data Visualisation (ggplot2)

Probability Distributions (actuar, distr)
Time Series Analysis (zoo, forecast)
Machine Learning (caret, xgboost)

RESTful APIs (plumber, OpenCPU)

Git expertise
Reproducible Data Science with Git
Apply a successful Git branching model


Every customer project is checked-in a Git repository. Our credo: The code is yours.
Free access to our Data Science Infrastructure with JupyterLab and GitLab CE included.


We help building your own Data Science software stack!

IaaS
AWS, Azure, GCP

on-premise with
Debian/Ubuntu,
Rocky Linux’/RHEL

Virtualisation
Docker, Kubernetes

Languages
R, Python, Julia

IDEs
JupyterLab + code-server
RStudio (on demand)

VCS
Git (GitHub, GitLab)


Check out our Jupyter demo environment at https://demo.jupyter.b-data.ch or run it locally with Docker Desktop.

docker run -it --rm -p 8888:8888 -v "${PWD}":/home/jovyan glcr.b-data.ch/jupyterlab/r/verse

Run the initial command in an empty directory so that the container populates it.
Visit http://127.0.0.1:8888/lab?token=<token> in a browser to load JupyterLab.


Projects

Below are the success stories of selected projects.


Contact

Phone number
Switzerland: +41 44 586 30 72
Denmark: +45 65 74 47 72

Business hours
Monday - Friday: 8:00 - 17:00