Leadership Power Tools: SQL, Statistics, and Data-Driven Decisions

This article explores how engineering leaders can leverage SQL and statistical methods for data-driven decision-making. The author points out that many engineering leaders are uncomfortable extracting and interpreting data, recommending learning SQL (e.g., using DuckDB) and statistical tools. The article covers summary statistics, distributions, confidence intervals, and Bayesian reasoning, demonstrating how to calculate confidence intervals by analyzing Firefox bug tracking data, using Monte Carlo simulations for project time estimation, and applying Bayesian inference to update project completion probabilities. The article emphasizes the importance of data analysis skills for engineering leaders, enabling more precise predictions and decisions.