toolkit

Skills

What I use to go from raw, messy data to a decision someone can make.

Core Tools
SQL

SQL / PostgreSQL

Joins, aggregations, CTEs, window functions (RANK, PARTITION BY), correlated subqueries, schema design.

Working knowledgeAdvanced
XLS

Advanced Excel

PivotTables/PivotCharts, INDEX/MATCH, XLOOKUP, SUMIFS/COUNTIFS/AVERAGEIFS, IFS logic, Power Query.

Working knowledgeAdvanced
PBI

Power BI

Data modeling and dashboarding for stakeholder-facing reporting.

Working knowledgeAdvanced
TB

Tableau

Interactive visualization and exploratory dashboards.

Working knowledgeAdvanced
PY

Python

pandas for cleaning and reshaping data, matplotlib/seaborn for visualization, Jupyter for exploratory analysis.

Working knowledgeAdvanced
pd

pandas & NumPy

DataFrames, groupby aggregation, merges and joins, missing-value handling, vectorized operations.

Working knowledgeAdvanced
GIT

Git & GitHub

Version-controlled, documented portfolio projects with public READMEs.

Working knowledgeAdvanced

// Databases & Querying

PostgreSQL SQL Joins Aggregations CTEs Window Functions RANK / PARTITION BY Schema Design pgAdmin

// Spreadsheets & BI

Excel Power BI Tableau PivotTables / PivotCharts INDEX/MATCH · XLOOKUP SUMIFS / COUNTIFS / AVERAGEIFS IFS Logic Power Query

// Python for Data Analysis

Python 3 pandas NumPy matplotlib seaborn Jupyter Notebook DataFrames & Series GroupBy & Aggregation Merge / Join / Concat Missing-Value Handling CSV & Excel I/O Exploratory Data Analysis

Active learning area — currently applying pandas to the same cleaning and analysis problems I solve in Excel and SQL.

// Analysis & Reporting

Data Cleaning & Validation Deduplication Anomaly Detection Missing-Value Treatment Benchmark & Variance Analysis Written Insight Reporting

// Tools & Workflow

Git & GitHub VS Code Version-Controlled Projects