tilmon-engineering

Systematic data quality remediation for duplicates, outliers, and inconsistencies.

Create effective visualizations for data analysis and reporting using DataPeeker.

Conduct systematic comparisons of segments, cohorts, or time periods to uncover meaningful differences.

Automatically identify foreign key relationships in relational databases using heuristics and analysis.

Systematic skill for investigating open-ended questions by breaking them into specific sub-questions.

Systematic approach to hypothesis testing for data analysis, ensuring scientific rigor.

Systematic exploratory data analysis to uncover patterns and insights in unfamiliar datasets.

Component skill for creating compelling data-driven presentations and whitepapers using marp and pandoc with proper citations and reproducibility

Master SQLite for data analysis with task-oriented guidance in DataPeeker.

Systematic CSV import process - discover structure, design schema, standardize formats, import to database, detect quality issues (component skill for DataPeeker analysis sessions)

Systematic skill for interpreting query results with intellectual honesty in DataPeeker analysis.

Use when conducting customer discovery interviews, user research, surveys, focus groups, or observational research requiring rigorous analysis - provides systematic 6-phase framework with mandatory bias prevention (reflexivity, intercoder reliability, disconfirming evidence search) and reproducible methodology; peer to hypothesis-testing for qualitative vs quantitative validation

Systematic marketing experimentation skill for validating concepts and generating actionable insights.

Component skill for systematic SQL query development in DataPeeker analysis sessions

Systematic data profiling and exploration skill for DataPeeker analysis sessions.