L3 AAQ in Data Analytics

OCR Level 3 Alternative Academic Qualification Cambridge Advanced National in IT: Data

Analytics (Certificate) is for students aged 16-19 years old. It will develop knowledge,

understanding and skills that will help prepare you for progression to undergraduate study when

taken alongside other qualifications and are relevant to the information technology sector.

You might be interested in this qualification if you want a small qualification to take alongside and

enhance your A Level studies, that builds applied or practical skills. You will have the opportunity to

apply what you learn to real-life contexts, such as:

• Planning, developing and reviewing spreadsheet data models that meet the needs of a client.

The qualification will also help you develop independence and confidence in using skills that are

relevant to the sector and that prepare you for progressing to university courses where

independent study skills are needed. You will develop the following transferable skills that can be

used in both higher education and other life and work situations:

• Developing communication skills through having to communicate ideas in different ways to

different stakeholders, much as you might be expected to in equivalent real-life situations.

• Developing creativity through opportunities for planning creative solutions that meet the needs

of different clients or end-users in the NEA unit.

• Developing skills of project-based working in the NEA unit. You are required to complete

individual tasks that combine to form a larger project. Managing different aspects of a project

effectively to ensure the success of the whole project is something you will likely encounter

should you go on to work in similar projects in higher education or work situations.

• Developing skills of time management. Time management is an important aspect of

completing projects successfully. You will need to manage your time effectively in the NEA unit

to ensure the needs of a client are met.

• Developing skills of reflective learning by reflecting on the choices you have made in the NEA

unit, and considering how you may approach similar tasks differently in future.

This qualification will complement other learning that you're completing at Key Stage 5. If you are a

full-time student, it will be part of your studies along with your A Levels.

OCR Level 3 Alternative Academic Qualification Cambridge Advanced Nationals in IT: Data Analytics

©OCR 2024 13

OCR Level 3 Alternative Academic Qualification Cambridge Advanced Nationals in

IT: Data Analytics Version 3 (June 2024)

All units in the qualification are mandatory. You must take all of these units:

• F200: Fundamentals of data analytics

This unit is assessed by an exam.

In this unit you will learn about the fundamental knowledge required for a career working in

data-related occupations. Topics include:

o Topic Area 1 Understanding data

o Topic Area 2 Managing data

o Topic Area 3 How data can be accessed and managed across platforms

o Topic Area 4 Legal considerations

o Topic Area 5 Job roles, skills and attributes in data analytics

• F202: Spreadsheet data modelling

This unit is assessed by an assignment.

In this unit you will learn the principles of data modelling with spreadsheets and the knowledge

and skills required to plan, design, create, test and review a spreadsheet modelling solution

that meets the needs of a specific client. Topics include:

o Topic Area 1 Principles of spreadsheet modelling

o Topic Area 2 Planning the design of a spreadsheet model

o Topic Area 3 Creating the spreadsheet model

o Topic Area 4 Delivering the outcomes

o Topic Area 5 Evaluation

At UTC Sheffield Olympic Legacy Park, the OCR Level 3 Alternative Academic Qualification (AAQ) Cambridge Advanced National in IT: Data Analytics is delivered through a mix of classroom teaching, practical data projects, and independent problem-solving tasks. Students learn in UTC’s specialist computing facilities and benefit from strong links with employer partners such as Siemens, IBM, and Sheffield Hallam University, which help connect classroom learning to real-world data challenges. Industry input and project-based learning give students the opportunity to apply analytical techniques used in professional settings, enhancing both technical and employability skills.

The qualification is made up of two mandatory units, each designed to build a complete understanding of data analytics in practice:

F200: Fundamentals of Data Analytics – Assessed by an external exam.

In this unit, students learn the core principles needed for a career in data analysis, including how to understand, manage, and access data across platforms. The unit also covers legal and ethical considerations and explores job roles and skills within the data analytics sector.

F202: Spreadsheet Data Modelling – Assessed by an assignment.

This unit focuses on developing practical data modelling skills using spreadsheets. Students learn how to plan, design, create, test, and review spreadsheet-based solutions for specific clients, applying the principles of data modelling, problem solving, and evaluation.

This combination of exam and coursework assessment ensures students gain both the theoretical knowledge and hands-on experience needed to progress into data-related university courses, apprenticeships, or careers in areas such as data analysis, business intelligence, and digital technology.

Grade 5 IT/Computer Science or Maths

Data Analytics opens a wide range of progression routes into higher education, apprenticeships, and employment across the digital, health, and sport sectors. The course equips students with analytical, technical, and problem-solving skills that are highly valued in industries increasingly driven by data.

Students can progress to university degrees or higher apprenticeships in areas such as Data Science, Computer Science, Business Analytics, Sport and Exercise Science, Public Health, or Health Informatics. Within UTC Sheffield Olympic Legacy Park’s specialisms, learners can use their data skills to support performance analysis in sport, healthcare data management, or research into population health and wellbeing.

Typical career pathways include roles such as Data Analyst, Performance Analyst, Health Information Specialist, Business Intelligence Officer, or Research Assistant, where graduates apply their knowledge of data modelling and interpretation to improve systems, performance, and outcomes.

This qualification provides an ideal foundation for students aiming to combine their interest in technology,