Data Analyst Course
Learn practical data cleaning, analysis, dashboards, and decision-ready insight reporting.
Course Overview
The Data Analyst programme helps learners turn messy information into practical insight. It focuses on the everyday analyst skills employers can assess: spreadsheets, SQL, cleaning decisions, statistics, dashboards, reporting, and clear recommendations.
Learners build portfolio evidence while learning how to explain assumptions, limitations, and responsible AI-assisted analysis without overstating what the data can prove.
Included Support
- 3-5 portfolio projects
- 1 capstone project
- CV + LinkedIn setup
- Job placement support (2-8 weeks)
- Access to job board/community
Who It Is For
- Graduates, job seekers, career changers, and early-career professionals who want a practical route into data analysis.
- Learners who are comfortable with structured problem solving and want to build evidence through dashboards, queries, reports, and case-study projects.
Learning Outcomes
- Clean and prepare datasets for analysis.
- Use Excel, SQL, and visualisation workflows to answer business questions.
- Build clear dashboards and written reports with limitations and recommendations.
- Use AI assistance responsibly for analysis planning, documentation, and review.
Curriculum
Beginner
Spreadsheet Analysis and Data Foundations
- Excel formulas and tables
- Pivot tables
- Data types
- Basic charts
- Analysis questions
Intermediate
SQL, Cleaning and Statistics
- SQL SELECT, JOIN and aggregation
- Cleaning missing and duplicate data
- Percentages and distributions
- Trend interpretation
- Data quality notes
Applied
Dashboards, Reporting and Portfolio Evidence
- Power BI or dashboard workflows
- Insight storytelling
- Responsible AI-assisted analysis
- Project documentation
- Capstone presentation
Tools and Technologies
- Excel
- SQL
- Power BI/data visualisation tools
- Python where relevant to the learner path
- AI assistants for review and documentation
Projects and Portfolio Outcomes
- Cleaned dataset analysis
- SQL question set
- Power BI-style dashboard
- Capstone insight report
Career Paths
- Junior Data Analyst
- Reporting Analyst
- Operations Analyst
- Data Support Analyst
Prerequisites
- No professional data experience required.
- Basic computer confidence and willingness to practise spreadsheets and structured thinking.
FAQs
Do I need previous data experience?
No professional experience is required, but regular practice with spreadsheets, queries, and reporting is important.
Does the programme guarantee a data analyst job?
No. The programme provides training, portfolio projects, CV and LinkedIn setup, job placement support, and access to a job board/community, but job outcomes depend on the learner, market, and employer requirements.
Is Python included?
Python is included where it is relevant to the learner path and project work. The core route prioritises Excel, SQL, cleaning, statistics, visualisation, and reporting.
Related Career Guides
How to Become a Data Analyst in the UK in 2026: Skills, Tools & Portfolio
A practical 2026 guide to becoming a data analyst in the UK, covering Excel, SQL, statistics, Power BI, Python, responsible AI use, and portfolio projects.
Data Analyst vs Business Analyst vs Data/AI Support: Which Career Path Is Right for You?
Compare data analyst, business analyst, and data/AI support paths by daily work, tools, strengths, portfolio evidence, and entry routes.
How to Build a Job-Ready Data Portfolio with Excel, SQL, Power BI and AI
Learn how to build a practical data portfolio using Excel, SQL, Power BI and responsible AI assistance, with project ideas and case-study structure.
Ready to discuss this programme?
Speak with Fekitech Academy about your goals, experience, and the right next step.
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