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Bringing Metadata to Life at Automattic with OpenMetadata
The metadata problem at scale Automattic’s data ecosystem is large and highly interconnected: thousands of Iceberg tables and views queried via Trino, thousands of Airflow tasks producing and updating them via Spark jobs, and a growing catalogue of Looker and Superset dashboards and charts on top. Most of the information about these assets exists somewhere, scattered…
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The WooCommerce Plugin Playbook: What Successful Stores Install, and When
Most plugin advice online is opinion‑dressed‑as‑fact: a list of “top 10 must‑have WooCommerce plugins,” usually written by someone selling one of them. We looked at hundreds of WooCommerce merchants who started a store in the past 12 months, and found a clear four‑phase pattern. At the same four points in their growth, stores reach for…
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Data Talks & Conferences Recommended by Automatticians
This post highlights specific data conferences and talks recently recommended by Automatticians (employees at Automattic). Staying informed is key in the fast-evolving field of data science. At Automattic, we value continuous learning and regularly attend conferences and talks that advance our understanding and skills. This post shares a curated list of events and talks that…
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From Support to Data Science and Analytics: My Journey at Automattic
“Is it possible to transform a role in customer support into a data science career?” This question, which once seemed like a distant dream, became my career blueprint at Automattic. This post describes the journey to a data wrangler in a tale of continuous evolution, learning, and adaptation.
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Hack Project: Creating a tool to translate customer feedback into product insights
Explore Automattic’s hack project in our latest post, where we developed a tool for analyzing Tumblr user feedback. Learn about our challenges with AI, creating insightful dashboards, and the impactful outcomes. Our collaborative effort not only enhanced product development but also earned us the top spot in our Hack Week Awards!
Data for Breakfast 