2. Create a space

Create a space

As discussed in the previous section, an organization contains one or more spaces. It is in these spaces where the actual data engineering happens. In this section, we'll set up a space and connect it to a data warehouse.

About spaces

The space is the environment where Y42 keeps all our pipelines and assets. Spaces are isolated working environments in an organization. We might create multiple spaces to separate data pipelines by functional teams or by varying levels of access restrictions to sensitive data.

In the background, spaces are connected to a data warehouse (BigQuery or Snowflake), a cloud storage bucket, and a Git repository. Y42 needs access to your data warehouse to read, process, and store your data. It uses the cloud storage as an intermediate layer to cache information. Lastly, the Git repository is where Y42 stores pipeline configurations, schedulers, tests, and metadata as code.

Data warehouseY42 writes the data it processes to a data warehouse and reads it again for further transformations.
Cloud storageY42 reads and writes data to a cloud storage bucket as an intermediate layer for caching information.
Git repositoryY42 writes the configuration of pipelines, schedulers, data tests, and metadata to a Git repository.

Sandbox mode

You can opt to create a space in sandbox mode. Doing so allows you to experience the Y42 platform without setting up the connection to a data warehouse. Please only use this for demo purposes, however! The space will automatically be deleted after 14 days and is not meant for real-life projects.

Create a space

Create a space

Every space in a organization has its own name. You'll be prompted to provide a display name when you create a new space. Based on this display name, Y42 will generate a slug. While you can modify display names after creation, this won't update the slug.

Connect to data warehouse and cloud storage

Y42 supports the following configurations:

Data warehouse providerCloud storage serviceReference
Google BigQueryGoogle Cloud StorageGuide
SnowflakeAmazon Web Services S3Guide
SnowflakeMicrosoft Azure Blob StorageGuide

Please refer to the relevant page for your configuration.

Connect to Git repository

After connecting to the data warehouse, we can choose the Git repository Y42 uses in the background. For this guide, let's stick with the default Y42-hosted GitLab repository. Please refer to the documentation if you want to use your self-hosted GitLab or GitHub repository.

Welcome to your space

After the configuration, Y42 will show us our newly created space. We'll explore the space in depth throughout the upcoming sections, but let's briefly discuss the different panels in our space.

Asset Editor

This is where the active development of our pipelines happens. We can use three distinct views: List, Lineage, and Code. Y42 keeps all three of these in sync, so edits in the lineage view will automatically show up in the code view. When developing, we can pick the view that best suits the current task and our preference.

Asset Monitor

Here we can zoom out and get a high-level overview of our asset health. Y42 displays relevant metadata and provides assets' build history. If something goes wrong with our pipelines, the asset monitor will show us. From the high-level overview we can drill down and get specific data on assets and runs.

Asset Catalog

The Catalog documents the assets in our space and displays all their relevant metadata. The lineage views here are especially useful, showing us how data flows through our pipelines at a column level.


As the name suggests, this is where we can view and adjust the settings for our space. This includes integrations, secrets, and access control. Note that Y42 has settings panels at both the space and organization level.

Ready for lift-off! 🚀

We now have an account, organization, and space all set up and ready for action! In the next sections, we'll explore all of the core features that Y42 offers on its turnkey data orchestration platform. We'll begin by setting up a pipeline that ingests and transforms data.