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Data Overload Vol. 9

Data Overload Vol. 9

Welcome to Data Overload Vol. 9, the monthly newsletter with company updates from Orchest!

The team grows 👥

In the month of April we have welcomed two new colleagues to our team: Nick joined as our Product Designer, and Bruno as Frontend Developer. We are thrilled to have them on board!

Orchest Kubernetes Operator available 🛠️

This has been a long time in the making and is a big step towards enabling Orchest users to install it in an existing k8s cluster of their choice. In addition, we are closer to shipping all the cool improvements from the past weeks to Orchest Cloud. Check out the new installation instructions and let us know what you think!

See you at PyCon Lithuania 🐍

Our talk "Beyond pandas: The great Python dataframe showdown" was accepted for the PyData track of PyCon Lithuania, so our colleague Juan Luis will travel to Vilnius to deliver it. You have a sneak peek in our blog, where we have already published reviews of Apache Arrow and Vaex. If you are attending the event, come and say hi!

Thank you!

We keep receiving super valuable feedback from our community of users, which keeps growing. Thanks to every one of you!

- Juan Luis Cano (Data Scientist Advocate)

Product updates

👁️‍🗨️ Improved Pipeline Editor view

Pipeline selection and editing are now integrated in a single view, reducing friction.

🗃️ Upload files to create new project

Now you can drag and drop an entire folder to create a project, or a bunch of files.

What we're reading

  • The Rise of Open Source Challengers (blog post)

    Why we like it: Rajko gives an overview on the current landscape of open source products competing with closed source alternatives in several areas (productivity apps, analytics solutions, tech infrastructure), discusses some trends in open source adoption and funding, and comments on why he thinks open source is winning. We wholeheartedly agree, and want to see more open source competition!

Orchest is an open-source project that simplifies the development and deployment of data pipelines. Get started for free or download the open-source version!