The Dataquest Download
Level up your data and AI skills, one newsletter at a time.
Hello, Dataquesters!
Here’s what we have in store for you in this edition:
Top tutorial: Upgrade your Docker Compose pipeline with security and production best practices. Read more
From the Community: SQL business insights, pandas tips, and ethical data visualization. Join discussion
What we’re reading: How RAG improves AI reliability, Python’s origin stories, and the pitfalls of “vibe coding”. Learn more
Take Your Docker Compose Setup from Local to Production-Ready
Got a multi-container pipeline running with Docker Compose? That’s a great start, but it’s not enough for production. In this advanced tutorial, you’ll learn how to harden your setup with health checks, multi-stage builds, non-root users, and externalized secrets. These upgrades don’t change what your pipeline does, but they make it safer, more portable, and easier to share with your team.
From the Community
Business Insights from the Chinook Database: Israel used advanced SQL and Excel to answer key business questions, topped with clear visualizations and a concise presentation of findings.
Alternative Way to Access DataFrame Columns: Hamza shared a lesser-known method for accessing pandas columns, useful when working with Python class instances.
The Importance of Truthful Data Visualization: Israel’s article explores how misleading charts can distort insights and why honest storytelling in data visualization matters.
DQ Resources
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
Analyzing Startup Fundraising Deals from Crunchbase: Learn how to process large CSV files efficiently by chunking, optimizing memory, and using encoding strategies, then turn the data into a fast, searchable SQLite database. Learn more
Answering Business Questions Using SQL: Learn how to analyze a digital music store’s data using SQL. This hands-on project with the Chinook database walks through real-world SQL tasks like tracking sales, evaluating employees, and spotting growth opportunities using CTEs, subqueries, and more. Learn more
What We're Reading
RAG Explained – SuperAnnotate: This article demystifies Retrieval-Augmented Generation (RAG)—a method that strengthens large language models by grounding them in external, up-to-date data. It highlights how RAG enhances factual accuracy, reduces hallucinations, and makes AI systems more reliable for real-world use.
The Problem with Vibe Coding – DEV Community: A thoughtful critique of “vibe coding,” where developers rely heavily on AI without understanding the underlying logic. The author warns that skipping the learning process may lead to shallow skills and a weaker sense of craftsmanship in software development.
Stories from Python History – TalkPython: A nostalgic and insightful roundtable with early Python contributors sharing how the language evolved from hidden side projects and 30-person PyCons to shaping open source at scale. You’ll hear the backstory behind “import this,” early web frameworks, and the rise of Jupyter, all threaded with humor, history, and the heart of Python’s community.
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