Finish Slime #22

Data Engineering, Analytics. No ML, no AI. The weekly dose of the data content you actually want to read!

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Great Recent Stuff

Becoming Pangea

Tristan Handy, founder and CEO of DbtLabs shares his vision for the data space in what he describes as a consolidation phase.

Data Activation Done – What’s Next?

This is the last part in a multi-part series on data activation. It’s all about why you’re doing data activation in the first place, including a bunch of use cases for it.

Cached Takes: 80% of Companies do not need Snowflake or Databricks

This article makes the case that most companies do not need fancy, expensive data solutions and would be better off working on boring stuff like data modeling.

Anomaly monitors and dbt tests to ensure the quality of business-critical pipelines

Anomaly detection is one way of increasing your data quality. This article provides a bunch of examples. While it uses the data monitoring tool Synq, you can implement these tests with any data monitoring tool.

Data: A Hoarder’s Storage Locker, Not a Magical Museum

“Most data pieces come with as much documentation as your sink of dirty dishes” - that quote describes this short piece well. Also, read the two linked articles from Cassey on data provenance and how to work with someone elses data. They pair well with this one.

Query your structured data in natural language.

Dataherald is a project enabling you to query SQL-based data warehouses with natural language.

How To Run dbt on Airflow

We added this story right to the dbt reading guide. It’s a complete intro to running dbt inside Airflow. One of many options (others are prefect or GitHub Actions).