Education and skills data
Education and skills data informs workforce planning, edtech and policy. This guide covers what exists and how to source it, with attention to the sensitivity of learner data.
Why education data matters
Skills shortages and workforce change make education and labour-market data strategic for employers, providers and policymakers. It links what people learn to what the economy needs.
The education data landscape
- Enrolment and attainment: participation and outcomes.
- Skills and labour market: demand and supply of skills.
- Provider and course data.
- Policy and funding statistics.
Common use cases
Workforce and skills planning, edtech product and content, policy and funding analysis, and labour-market intelligence.
Sourcing considerations
Official statistics are rich but aggregated; learner-level data is sensitive (often special-category or children data) and tightly controlled. Skills data from job postings needs methodology scrutiny. Harmonising classifications is central.
Delivery and governance
Most use cases use batches. Learner data demands strict lawful basis, aggregation or anonymisation, and care with children data. Provenance matters for policy use.
In a managed model
A managed partner can combine official, labour-market and skills data responsibly, defaulting to aggregated forms.
Sensitive by default
Official education statistics are rich but aggregated; learner-level data is sensitive, often special-category or relating to children, and tightly controlled. The responsible default is aggregated forms, with strict lawful basis and care where children’s data is involved. Skills data drawn from job postings needs methodology scrutiny before it is trusted.
Harmonisation and use
Classifications and geographies vary, so harmonisation is central to combining sources for workforce planning, edtech, policy and labour-market intelligence. Provenance matters for policy use, and personal data must be handled lawfully throughout.
- Skills shortages make education and labour-market data strategic.
- Official statistics are aggregated; learner-level data is sensitive.
- Skills data from job postings needs methodology scrutiny.
- Default to aggregated forms; take special care with children data.
Sources & further reading
- Eurostat and Cedefop: education and skills statistics.
- OECD: education data (PIAAC, PISA).
- National education authorities.
- EUR-Lex: Regulation (EU) 2016/679 (GDPR).
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