High Drop-out Rate Alert
25% of students drop out or transfer from this specific course. Consider asking why on an open day.
DipHE Data Analysis
About this course
Data analysis is the discipline of extracting meaning from information. In almost every sector of the modern economy, decisions that were once made on intuition or experience are increasingly guided by systematic analysis of data: health services use it to understand patient outcomes, businesses use it to understand customer behaviour, governments use it to evaluate policy, and researchers use it to test hypotheses. The ability to collect, clean, interpret, and communicate data is one of the most sought-after capabilities in the contemporary labour market. The Open University's programme in data analysis is offered on a part-time basis and delivered through distance learning, making it accessible to students who are studying alongside work, family commitments, or other responsibilities. You will develop a grounding in the core concepts and methods of data analysis, including statistical reasoning, data visualisation, and the use of computational tools to work with large and complex data sets. The programme develops both the technical skills needed to handle data and the critical thinking needed to interpret it accurately and honestly. You will learn how to ask the right questions of a data set, how to choose appropriate methods of analysis, and how to present findings clearly and persuasively to different audiences. The Open University's long experience in distance learning means the programme is designed for flexibility and supported study. Data analysis graduates find opportunities across an extraordinarily wide range of sectors. Roles in business intelligence, financial analysis, health data, marketing analytics, public policy, and research are all open to graduates with strong analytical skills and the ability to work with data confidently. The programme is also well suited to professionals who want to formalise and extend skills they are already developing in the workplace. Further study in data science, statistics, or applied computing is a natural progression for those who want to specialise further.
Syllabus & Modules
Typical curriculumStudent Satisfaction
National Student Survey - 20 respondents (56% response rate)
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