Seventeen projects on real data
Life-sciences studies, data cleansing and de-duplication, business decisions and visual analytics. Each one ships with a project document, a data sheet and the raw data it was built from.
How I work with data
The same five stages run through every project on this page, from a one-off analysis to an autonomous data quality platform.
- 01
Profile
Measure completeness, validity, consistency and uniqueness before anyone touches a value.
- 02
Diagnose
Trace each defect to its root: a missing rule, a unit mix-up, a site-specific habit, a broken feed.
- 03
Heal
Fix with rules mined from the data itself. Confident fixes run automatically; the rest go to a data steward.
- 04
Govern
Every change gets an audit trail, an owner and a confidence score, so the fix is trusted and repeatable.
- 05
Explain
Turn clean data into views and recommendations people read in seconds and act on.
Where I can help
Life-sciences & clinical data
Patient record matching, multi-site data harmonisation, trial reporting tables, survival analysis and surveillance data cleaning.
Master data & data quality
Material, customer, vendor and site master design, SAP material master structures (MARA, MARC, MAKT, MARM), DQ scorecards and steward workflows.
Business problem solving
Experiments, churn and retention economics, operational KPIs: a clear question, a defensible method and a recommendation with a way to measure it.
Analytics & visualization
Dashboards, 3D and interactive data stories in Python, SQL, D3 and Power BI, designed for the question the audience is asking.
Have data that needs fixing, or a question that needs answering?
I work with teams on data quality programmes, master data clean-ups, clinical and life-sciences data, and analytics that people actually use.