Skill Profile
Data Management
"Structuring, storing, cleaning and controlling access to datasets so they remain accurate, findable and usable by the people and systems that depend on them."
YOUR SKILLS
Problems This Skill Solves
- Duplicate, missing or inconsistent data across systems undermining trust in reports
- Data too disorganised to be reused for new analysis or research
- Unclear ownership of a dataset leading to unmanaged access or version conflicts
- Regulatory or research requirements for structured, auditable data handling
Data management is just storage — where files live.
Most of the work is structure, quality and access control, not physical storage location.
Clean data stays clean once organised.
Data quality decays continuously as new entries come in; ongoing maintenance is required.
Research & Outlook
Growing regulation and AI systems' hunger for high-quality training data are both increasing demand for people who can structure and govern data reliably.
See This Skill In Action
Watch a professional demonstrate Data Management in a real working environment — what it looks like, how it's applied, and why it matters.
Technical / Data
Data Management
Also Known As
Growth Path
Enters and organises data correctly following an existing structure.
Designs data structures, cleans and validates datasets and manages access controls.
Sets data architecture and governance standards across an organisation, balancing usability, quality and compliance.
How to Practise
- 1.Clean and structure a messy real-world dataset, documenting each transformation step
- 2.Design a simple database schema for a real use case and populate it with sample data
- 3.Write a data dictionary describing every field in a dataset you maintain
- 4.Practise setting and auditing access permissions on a shared dataset
How to Prove
- ·A before/after example of a messy dataset you structured and documented
- ·A relevant qualification in data management or health informatics
- ·Evidence of maintaining a dataset used reliably by others over time