HomeFor your teamData

For your teamData

If you have data, here is how I would start.

I turn messy data into decisions. I taught myself SQL and Python on my own business, built a public dashboard from real datasets with every analysis checked against its source, and I am Google Data Analytics certified. This is how I would spend my first 90 days on your team.

Lane
Data
Code
SQL (PostgreSQL, BigQuery, MySQL), Python, R and RStudio
Dashboards
Tableau, Looker Studio, Power BI
Built
A public data dashboard: ten analyses, each with its source, period and licence
Also
Google Data Analytics Professional Certificate

On wide screens the first 90 days is drawn as a trajectory that follows your scroll, with three stages: T+30, T+60 and T+90. Each stage is also written out below as text.

T+0 to T+9030-60-90 plan

The first 90 days

What I would do in a new data role, in the order I would do it. A plan, not a promise about any one employer.

  1. T+30 · Learn

    Learn the data and the questions

    Find where each dataset comes from, how it is cleaned and who asks what of it. Write down the definitions so everyone counts the same way.

    On my dashboard, every analysis lists its source, period, licence and caveat.

  2. T+60 · First deliverable

    Deliver one analysis or one fix

    One analysis with its question, query, chart and caveat, or a fix for a report that is slow, wrong or ignored. The checks sit next to the result.

    Each analysis on my dashboard was checked against its primary source.

  3. T+90 · Own it

    Own a recurring report

    Run one report or dashboard on a schedule, with a refresh, checks and a short note on what changed. Document it so it survives a handoff.

    My dashboard shows when its data was refreshed and when each source releases next.

  1. T+0 Day one
  2. T+30 Learn
  3. T+60 First deliverable
  4. T+90 Own it

02Work to read first

The three cases and three analyses closest to this work.

Case studies My own work and my past roles

Analyses on public data See all ten on the dashboard

03Matching skills

The skills and tools I would use.

Query and code

  • SQL (PostgreSQL, BigQuery, MySQL)
  • Python
  • R and RStudio
  • Excel (pivot tables, VLOOKUP, XLOOKUP)
  • Google Sheets

Dashboards

  • Tableau
  • Looker and Looker Studio
  • Power BI
  • Weekly reporting on outreach, conversion rates and revenue

Method

  • Google Data Analytics Professional Certificate
  • Analyses checked against primary sources
  • GA4 and Google Search Console
  • AI tools used regularly for research and writing

Every skill with its tools and proof is on the Skills page, and the full route is on About.

04Contact

Tell me which dataset or report to look at first.

Open to e-commerce, data and operations roles. Los Angeles or remote.