OCR H019/H119

Data Analytics

OCR Cambridge Advanced National in IT: Data Analytics. Both externally assessed units covered topic area by topic area: F200 Fundamentals of data analytics and F201 Big data and machine learning, with quizzes, graphs, interactive models and exam-style questions.

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10Topics

100Quiz questions

186Exam marks

Distinction starTarget grade

Your route to Distinction star

Revision works when it has an order. Follow these stages rather than opening topics at random.

Know which unit you are sitting, and its shape

F200 is 1 hour 15 minutes for 60 marks and samples across all five topic areas. F201 is 1 hour 30 minutes for 60 marks. Roughly a mark a minute, so a six mark question gets six minutes and no more.

Be precise with vocabulary

Data against information. Validation against verification. Precision against recall. Controller against processor. At Level 3 the exact term is the mark, and a paragraph of description around a missing word earns less than the word.

Learn the confusion matrix properly

Being able to calculate precision and recall from four numbers, and then say which one matters for the scenario and why, is the single most reliable source of marks in F201.

Apply the law, do not recite it

Name the Act or the principle, apply it to the scenario in front of you, and reach a conclusion about what has to change. Listing the seven principles untouched by the scenario scores a fraction of that.

Answer the command word

State and identify want a name. Describe wants detail. Explain wants a reason. Calculate wants working shown. Discuss and evaluate want both sides and a judgement, and the judgement is where the top band is.

Always end with the decision

Analytics exists to change a decision. Whether the question is about a chart, a pipeline or a model, the answer that says what should now happen differently is the answer in the top band.

Exam unit 5 topics

F200: Fundamentals of Data Analytics

Externally assessed: 1 hour 15 minutes, 60 marks, 75 guided learning hours. Understanding data, managing data, platforms and access, the law, and the roles.

F200 TA1F200 TA1: Understanding DataWhat data actually is, how it differs from information and knowledge, the types it comes in, and the formats it is stored in.F200 TA2F200 TA2: Managing DataThe data lifecycle and the analytics pipeline, how data is gathered, stored and transformed, and what data quality actually means.F200 TA3F200 TA3: Accessing Data Across PlatformsAPIs, interoperability, access control and the cloud: how data gets from one system to another, and who is allowed to see it.F200 TA4F200 TA4: Legal ConsiderationsThe UK GDPR and the Data Protection Act 2018 applied to real analytics work, plus the other legislation an analyst has to know by name.F200 TA5F200 TA5: Job Roles, Skills and AttributesWho does what in a data team, the technical and personal skills each role needs, and how to communicate a finding to somebody who will not read the method.

Exam unit 5 topics

F201: Big Data and Machine Learning

Externally assessed: 1 hour 30 minutes, 60 marks, 70 guided learning hours. The scope of big data, its infrastructure, machine learning and AI, ethics, and the environment.

F201 TA1F201 TA1: The Scope of Managing Big DataWhat makes data big, where it comes from, and the effect it has on organisations, individuals and whole sectors.F201 TA2F201 TA2: The Infrastructure Challenges of Big DataStorage, network and processing at a scale where one machine is not an option, and the trade-offs each choice forces.F201 TA3F201 TA3: Big Data with Machine Learning and AIWhat machine learning actually is, the three kinds of learning, how a model is trained and tested, and how to tell whether it works.F201 TA4F201 TA4: Legal and Ethical Issues in Data ManagementWhat changes legally and ethically when the dataset is enormous and a model is making the decisions: bias, transparency, profiling and accountability.F201 TA5F201 TA5: Environment and SocietyWhat all this computing costs the planet, what green computing can actually do about it, and how big data is changing work and society.