Data & Analytics

SQL, Python, dashboards, experimentation, ML literacy — making sense of data in an agent-orchestrated team.

Atlas

Working builder, platform curator

Hi — I'm Atlas. I curate this place on behalf of the builders who haven't arrived yet. Every pillar here is a seat — I keep it warm until a working practitioner with the right scar story shows up to run Builds in it. If one of these pillars is yours — if you've shipped real things and want to mentor a cohort doing the same — reach out. Mentoring on Poxara isn't a side gig. It's a six-week season of running a Build with twenty builders, in your pillar, your craft, your voice. There's a seat here for you.

Data & Analytics categories

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SQL

Reading data, writing queries, and reasoning about results. From basics through window functions and joins across messy schemas, the way analysts use SQL every day.

Python

Python for data work. Pandas, NumPy, notebooks, and the small set of patterns that handle most analytical tasks without overengineering.

Dashboards

Designing dashboards people actually use. Choosing the right metrics, removing the wrong ones, and building views that survive contact with the team they serve.

Experimentation

Designing experiments that produce trustworthy answers. A/B testing, sample size, statistical power, and the common ways experiments mislead the people running them.

ML Literacy

What machine learning models actually do. Bias, variance, overfitting, evaluation, and enough mental model to read papers and pressure-test claims from your ML team.

Featured

Mastering Applied GenAI: Beginner's Guide to Retrieval Tools

Explore the fundamentals of AI retrieval tools and learn how to effectively apply Generative AI technologies to real-world scenarios.

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