The Dataquest Download
Level up your data and AI skills, one newsletter at a time.
Hello, Dataquesters!
Here’s what we have for you in this edition:
Top Read: Learn how Kubernetes keeps your apps running smoothly with stable networking, rolling updates, and zero downtime. Read the blog
Community highlights: From data-driven insights in global markets to creative survey analysis and practical Python tricks. Join the discussion
What we’re reading: How AI could reshape pricing, how researchers are applying computer vision to biodiversity, and what happens when AI goes rogue. Learn more
Today we’ll solve a core networking puzzle in Kubernetes: how do you keep applications connected when Pods crash and restart with new IPs? And just as important, how do you deploy updates without breaking your users?
In this tutorial, we’ll walk through a realistic data pipeline scenario where a PostgreSQL database must remain accessible while an ETL application is updated. You’ll learn how Services provide stable networking, how rolling updates enable zero-downtime deployments, and how Namespaces keep environments organized—all essential features for running production-ready Kubernetes systems.
From the Community
Optimal Yuan Acquisition 2025: Strategic Exchange Guide for Euro-Holding International Students in China: The project of Alejandro stands out for its descriptive title, accurately selected data source, explicitly stated project goal and questions to answer, well-outlined problem background, detailed and multifaceted data analysis, excellent narrative, insightful plots, and clearly presented recommendations.
Star Wars Survey: Parth published an amazing, perfectly structured project that showcases their deep curiosity in the data and strong analytical skills, meticulously described methodology and steps to take at each stage of the project, well-discussed intermediate and final findings, and stunning visualizations.
Improving Readability of Large Numbers in Python: Linky posted a helpful trick on how to suppress scientific notation in Python pandas and display large numbers in a user-friendly decimal format, with a specified number of decimal places.
5 Hard-Earned Lessons Every Aspiring Data Scientist Must Know: Hamza shared an insightful article written by a seasoned data scientist, a former career-changer, offering precious lessons that could save you years of struggle and thousands of dollars.
Project Tutorials
Star Wars Survey Analysis Using Python and Pandas: Learn how build professional-quality visualizations that tell a compelling story about Star Wars fandom, demonstrating how proper data cleaning and thoughtful visualization design can transform raw survey data into stakeholder-ready insights. Learn more
Finding Heavy Traffic Indicators on I-94: Learn how to build multiple visualizations that tell a comprehensive story about traffic patterns, demonstrating how exploratory data analysis can reveal insights that summary statistics alone might miss. Learn more
What We're Reading
AI at Rent the Runway: A thought experiment on how AI could have reshaped Rent the Runway’s 2020 dynamic pricing model compared to what the data science team used then.
AI Sees Nature Differently: Researchers at the Alan Turing Institute built Scivision, a catalogue of pre-trained computer vision models designed for biodiversity and environmental studies.
When AI Went Rogue: A developer’s experiment turned into chaos when their AI deleted data, fabricated 4,000 fake users, and lied to cover it up—a stark warning about unchecked AI autonomy.
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High-fives from Vik, Celeste, Anna P, Anna S, Anishta, Bruno, Elena, Mike, Daniel, and Brayan.