Fresh data insights from Automattic.
Dive into our blog where we turn complex data into clear, actionable insights. Stay tuned for fresh perspectives and expert advice from the heart of Automattic’s data team.
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Data Speaker Series: Charles Earl on Discriminatory Artificial Intelligence
Charles Earl on identifying and overcoming bias in machine learning.
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Easier A/B Tests with Automattic’s Own Tool, Hypotheses
Sirin Odrowski introduces you to how we run A/B tests at Automattic using a tool we built called Hypotheses.
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This Week in Data Reading (and Watching!)
This week, we’re bringing you links from Charles, Simon, and Carly featuring neural networks, a video advocating for morality in algorithms, and incredible music made by machines.
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Data Speaker Series: Thorsten Dietzsch on Building Data Products at Zalando
In the first of our Data Speaker Series posts, Thorsten Dietzsch shares how data products are managed at Zalando, a fashion ecommerce company.
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How Communication Density Fuels Automattic
How does meeting in person affect our interpersonal communication at Automattic? Demet Dagdelen reveals all.
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This Week in Data Reading
This week, Sirin, Boris, and Demet have some recommended reading for you in the fields of descriptive data analysis, machine learning, and artificial intelligence.
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Real-Time Elasticsearch Indexing on WordPress.com
Love databases, indexing, and Elasticsearch gymnastics? Greg Brown walks us through the indexing sausage factory on WordPress.com.
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data.coalesce() — Automattic Data Division Meets in Montréal
Want to know what Automattic data wranglers do when they meet up? Carly Stambaugh takes you behind the scenes.
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Time Series Analysis: When “Good Enough” is Good Enough
Anomaly detection and time series forecasting are valuable in monitoring the financial and technical health of an organization. Proper modeling of time series requires accounting for periodic fluctuation; malicious users; data irregularity, saturation or scarcity; sudden peaks and drops. To account for these parameters, the modeler needs to select the proper model family, optimize the…
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This Week in Data Reading
This week, Charles, Xaio, Chris, and Boris share pieces on machine learning, MySQL, pop lyrics, and career advice.
Data for Breakfast 