Analytics Engineer · Super Intelligence
35 articles · Page 4 of 5
A practical guide to generating sequences, running simulations, and working with random numbers in R — covering seq(), sample(), runif(), and when each tool is the right one.
Six research-backed leadership principles, from self-awareness and productive conflict to emotional intelligence, with practical applications for analysts and technical leaders.
How Kroger built its retail data operation, from the SSOT-MVOTs framework to 84.51°, Kroger Precision Marketing, and digital shelf technology, along with the questions those practices raise.
A hands-on walkthrough using real Chipotle order data — loading, aggregating, and visualizing purchase patterns with R and ggplot2.
Random sampling, reproducibility, subsetting, and counting outcomes — all through a simple coin flip simulation. The concepts here apply everywhere in data analysis.
Generate synthetic data, compute descriptive stats, filter by condition, and cap outliers using winsorization — the core data cleaning toolkit in base R.
Over 1.3 million new artists, 17 million new tracks, and platforms that didn't exist a decade ago. A summary of what Chartmetric's 2023 report shows about the state of the music industry.
Analytics engineer turning fragmented tidbits into confidence: messy data structured, patterns caught early, answers made plain with AI.
Copyright 2026 Christopher A. Rotunno. All Rights Reserved
