IT: Data Analytics (AAQ)

This exciting new course is designed for students who want to develop applied knowledge and skills in data analytics. It blends theoretical understanding with hands-on experience, preparing learners for higher education or careers in IT, business analytics and digital marketing. You’ll explore how data is gathered, processed, visualised, and used to make decisions in real-world contexts.

Students studying three A Levels and/or AAQs will be expected to have a minimum of two GCSEs at grade 5 and three at grade 4, including English Language and Mathematics.

You’ll develop the analytical, technical, and problem-solving skills that drive the modern digital world.

Key topics include:

• Fundamentals of Data Analytics – understanding how data is collected, processed, and used to make business decisions.

• Big Data and Machine Learning – exploring how organisations use large datasets and AI tools to gain insights.

• Spreadsheet Data Modelling – applying advanced functions and data tools to model and interpret information.

• Optional Specialist Units:

• Relational Database Design

• Data Visualisation

• Data and the Internet of Everything

• Data and Digital Marketing

• Combines academic and vocational learning.

• 40% external assessment, 60% coursework.

• Flexible unit choices to suit your interests.

• Builds transferable skills like communication, problem-solving, and project management.

• Designed to complement A Levels and other Level 3 qualifications. This qualification builds theoretical and practical understanding relevant to study in IT or data-related fields. It covers data analytics, Big Data, spreadsheets, databases, the Internet of Everything, and digital marketing. The qualifications are assessed holistically and include both external exams and Non-Exam Assessment (NEA) units, using the Pass, Merit, Distinction, and Distinction* grading scale.

• Exams: Two units, Fundamentals of Data Analytics and Big Data and Machine Learning, each 1 hour 15 minutes.

• Coursework: Three NEA units assessed by your teachers and moderated by OCR.

• Assignments are practical and based on real-world scenarios.

• You can resubmit coursework once and resit exams twice.                                                  

• Exam Board - OCR Cambridge

• Take part in IT workshops.

• Complete employer linked work related projects in IT-related industries.

• Guest lectures from data professionals.

• Workshops on AI, machine learning, and data ethics.

• Opportunities for work experience in IT, marketing, or analytics roles.

• Expert teaching from experienced IT professionals.

• Access to industry-standard software and facilities.

• A supportive learning environment focused on your progression.

• Strong links with universities and employers.