Data profiling
Data profiling is about understanding what your data actually looks like before you try to use it.
It provides a clear picture of structure, content, and quality, helping to identify issues early and avoid incorrect assumptions during analysis or reporting.
When data profiling is useful
Data profiling is particularly helpful when:
- You’ve inherited data you didn’t create
- A dataset has grown over time and lacks clear documentation
- Reports or analysis produce unexpected results
- You’re planning data cleansing, transformation, or integration work
Profiling helps establish a solid starting point before changes are made.
What I typically help with
I review datasets to build an accurate picture of their shape and condition. This commonly includes:
- Assessing field structure and data types
- Identifying patterns, ranges, and outliers
- Highlighting missing or inconsistent values
- Summarising key characteristics of the data
The outcome is clarity about what the data contains and where potential problems lie.
What you can expect
When we work together:
- You get a clear, plain-English overview of your data
- Issues and risks are identified early
- Recommendations are practical and proportionate
The aim is understanding first, so any follow-on work is based on evidence rather than guesswork.
Next steps
If you need to understand the true state of your data before making decisions or changes, get in touch and outline what you’re working with.