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Skill Profile

Data Analytics

Technical / Data

"Examining datasets—cleaning, querying, visualising—to identify patterns, trends or anomalies that answer a specific business or research question."

YOUR SKILLS

Problems This Skill Solves

  • Decisions being made on gut feeling when the data to answer the question already exists but isn't being used
  • Poor campaign or product performance going unnoticed until it's too late to act
  • Data spread across disconnected systems with no single reliable view
  • Misleading conclusions drawn from data because of flawed analysis or visualisation
Myths vs Truths
Myth

More data always means better analysis.

Truth

Poor quality or irrelevant data adds noise; a smaller, well-understood dataset often produces more reliable insight.

Myth

Data analytics is just building dashboards.

Truth

The valuable part is framing the right question and interpreting what the numbers actually mean for a decision.

Research & Outlook

AI copilots embedded in BI tools now generate first-draft charts and summaries from plain-language questions, shifting analysts' time towards validating outputs and communicating nuance to stakeholders.

See This Skill In Action

Watch a professional demonstrate Data Analytics in a real working environment — what it looks like, how it's applied, and why it matters.

Data Analytics in practice
A professional demonstrates this skill on the job
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Technical / Data

Data Analytics

0roles unlock with this skill

Also Known As

Business intelligenceData analysisAnalytics

Growth Path

Beginner

Cleans data and produces basic charts or summary statistics to answer a defined question.

Intermediate

Builds dashboards and runs deeper statistical analysis to uncover trends and drivers behind a metric.

Expert

Designs analytics strategy across an organisation, builds predictive models, and shapes decisions at leadership level with data.

How to Practise

  • 1.Take a public dataset (e.g. from data.gov.uk) and produce a short analysis answering a specific question
  • 2.Write SQL queries against a sample database to answer increasingly complex business questions
  • 3.Build a dashboard in Power BI or Tableau that updates from a live or refreshed data source
  • 4.Practise explaining a statistical finding to a non-technical audience in plain language

How to Prove

  • ·A portfolio of dashboards or analyses with a clear before/after decision impact
  • ·A recognised qualification or certification (e.g. Google Data Analytics Certificate, Microsoft Power BI certification)
  • ·Evidence of a specific business decision changed by your analysis