ICTQual AB Level 4 Diploma in Data and AI-Data Analyst
The ICTQual AB Level 4 Diploma in Data and AI – Data Analyst is a comprehensive qualification designed for learners aspiring to turn data into insight-driven solutions. This Level 4 diploma equips learners with practical expertise in data collection, cleaning, analysis, visualisation, and the ethical application of AI tools to support informed decision-making.
Throughout the course, learners build advanced technical skills, such as working with structured datasets, performing statistical analysis using industry-standard software, and interpreting data trends. The curriculum emphasises the importance of accuracy and data governance alongside analytical thinking, ensuring that learners are prepared to support business strategy with integrity and clarity.
Ideal for those targeting roles in data interpretation or support, this diploma also lays the groundwork for roles including Data Analyst, Business Intelligence Assistant, or AI Data Specialist. Learners emerge with transferable capabilities in quantitative analysis, storytelling with data, and real-world problem-solving.
By completing this qualification, learners gain a solid foundation to drive strategic initiatives and enhance organisational performance using data. Whether progressing academically or entering the workplace, this diploma represents a dynamic pathway into the expanding field of data-driven decision-making.
Level 4 Diploma in Data and AI-Data Analyst
To enrol in ICTQual AB Level 4 Diploma in Data and AI-Data Analyst, learner must meet the following entry requirements:
This qualification, the ICTQual AB Level 4 Diploma in Data and AI-Data Analyst, consists of 6 mandatory units.
- Data Collection, Cleaning & Preparation
- Statistical Analysis & Trend Identification
- Data Visualisation & Reporting
- Introduction to AI Modelling & Applied Tools
- Data Governance, Ethics & Quality Assurance
- Business Insight & Decision-Support Applications
Learning Outcomes for the Study Units:
1. Data Collection, Cleaning & Preparation
- Apply appropriate techniques to collect reliable and relevant data from diverse sources
- Clean and preprocess datasets using standard tools, including handling missing, inconsistent, or erroneous data
- Structure and prepare datasets for further analysis, ensuring accuracy and usability in data modelling tasks
2. Statistical Analysis & Trend Identification
- Apply descriptive and inferential statistical techniques to identify patterns, trends, and correlations in data
- Interpret statistical outputs using critical thinking to draw meaningful insights
- Utilise quantitative techniques—such as averages, variances, and correlation coefficients—to aid strategic decision-making
3. Data Visualisation & Reporting
- Create clear and engaging visualisations (e.g., charts, graphs, dashboards) to present data insights effectively
- Tailor reports and visual outputs for varied audiences, ensuring clarity and informed understanding
- Summarise analytical findings in written and visual formats to support evidence-based recommendations
4. Introduction to AI Modelling & Applied Tools
- Understand fundamental AI concepts and their relevance to data analysis
- Apply basic AI modelling tools or techniques (e.g., simple regression, classification) under guidance
- Recognise the applicability and limitations of AI models within business and organisational contexts
5. Data Governance, Ethics & Quality Assurance
- Explain the principles of data governance, including compliance, stewardship, and key regulatory frameworks
- Embed ethical considerations into data analysis processes, such as fairness, privacy, and transparency
- Implement quality assurance measures to maintain integrity and consistency across data workflows
6. Business Insight & Decision‑Support Applications
- Translate analytical findings into actionable business intelligence tools or recommendations
- Support decision-making through data-driven insights aligned with strategic objectives
- Reflect on how data-based insight contributes to organisational performance and continuous improvement
The ICTQual AB Level 4 Diploma in Data and AI – Data Analyst equips learners with advanced, workplace-ready skills in data analytics, AI application, and decision-support systems. Upon completion, learners are well-positioned to progress academically or professionally within the data, digital, and AI sectors.
Academic Progression Opportunities
Graduates of this diploma may advance to:
- Level 5 Diplomas in Data Science, Applied AI, Business Intelligence, or Software Development
- Professional certifications in data analysis, data visualisation, Python, SQL, or AI tools
- Higher-level apprenticeships in roles such as Data Analyst, Business Intelligence Developer, or Machine Learning Technician
Career Development Opportunities
This qualification opens doors to entry-level and junior analyst roles, including:
- Data Analyst
- Business Intelligence Assistant
- Data Reporting Officer
- AI Support Analyst
- Operations Data Coordinator
Learners may find employment across industries such as:
- Finance and Banking
- Retail and E-commerce
- Healthcare and Pharmaceuticals
- Government and Public Sector
- Logistics and Manufacturing
Professional Skills Gained
On completing this diploma, learners will have:
- Strong proficiency in data cleaning, analysis, and visualisation
- Basic working knowledge of AI models and digital tools
- An understanding of ethical data handling and governance
- Strategic insight to support data-led business decisions
