Introducing a new interface for managing your SQL data models in Snowplow Insights

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Modeling raw data into various derived tables for different use cases is a key step in deriving value from your Snowplow data. Whether you are using our out of the box web and mobile data models or a custom data model, you can run these via sql runner as part of your Snowplow Insights pipeline.

A new interface for managing your SQL data models

We are excited to introduce our newest interface in the Snowplow Insights console, a UI for configuring and deploying data models:

While the SQL and playbooks for your data models will still be hosted in your snowplow-pipeline GitHub repository, you’ll be able to manage all model configuration in the Insights console, including the schedule, owners and lock type:

You will also be able to specify which playbooks will run as part of a data model, in what order and with what dependencies (linear or parallel):

Of course, you can then continue to monitor the data model runs in the ‘Jobs’ interface as described in this blog post.

What’s next

This new interface is the first step in better integrating the management of your data models with the management of the rest of your Snowplow Insights pipeline. Later this year, we will be working on expanding this functionality, including:

If you have any questions, comments or suggestions about these upcoming developments, get in touch with your Customer Success Manager, or take a look at our public roadmap on GitHub.

Getting started

More information on how to use the new data modeling interface can be found in the technical documentation.

If you are already a Snowplow Insights customer, we will be contacting you about upgrading to the new interface. Not a Snowplow Insights customer yet? Get in touch with us here to learn more, or sign up for free to try Snowplow today.

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