Think about the cost of data validation errors 🚧: at worst, they take down entire systems through runtime errors.

Pydantic is a framework for data validation to prevent downtime.

Read an overview of how to use Pydantic in tandem with Prefect:
vist.ly/xd7j

Mike Grabbe (Principal Data Engineer) went from MS SQL Server jobs to scalable Python orchestration to unblock his company's data science team.

Come to ODSC in Boston April 23rd to find out how he did it with Prefect!

Find out more here 👇
vist.ly/x4j9

If you have code that:

🛣️ Is used as a routing mechanism
🤖 Unifies remote systems
🚧 Relies on systems with transient issues

That is glue code. Instead of deploying brittle code, incorporate it as part of your core workflows with Prefect.

Read how 👇
vist.ly/vmrz

Need a reason to come to Boston besides the amazing bakeries in the North End?

Join us at Open Data Science's Data Engineering Summit on Wed 4/24 at 11am to hear from Bill Palombi and Jeff Hale on managing data pipelines like a platform.

Sign up today!
vist.ly/v4j2

Prefect will be in Boston April 23-25 for ODSC East (by Open Data Science)!

Chat with us at booth #17, hear about how to successfully build a self serve data platform from our team and from a user's perspective.

Register here and join us ➡️ vist.ly/tr46

Want to schedule checks for web vulnerability scans? Do so with Prefect.

Check out Oussama's full code below. Copy the code, pass in your custom domain, and schedule daily 👇

vist.ly/td2g

Prefect's workflow metrics got more performant. How? Being backed by ClickHouse 🏃

Last week, Adam Azzam presented at the Clickhouse meetup (hosted by Ramp) about our swiss-army knife for data engineers: events.

👂 Listen to the full talk here:
vist.ly/t73c

You have data pipelines that need to be monitored so you stand up alerting infra. But then that system goes down. Now what?

We built observability into Prefect to manage this pain point for data pipelines and workflows. Read through the best practices👇

vist.ly/s7j9

Are you sick of a Status field showing up as either “Fulfilled” or “Fulfillment” depending on the source? If so, you need enum validation.

At Prefect, we ❤️ Pydantic. In this iteration, we explore enums and how they can be used for better data quality.

vist.ly/38z4x

Ever find hidden #Python dependencies for your dbt models? Use Prefect with #dbt and #Snowflake to:

⧯ Get reliability with central logs
💲Find your least timely runs through Prefect's metrics
🔜 Trigger models through APIs when needed

Read our guide 👇
vist.ly/37hzh