Data analytics and Big Data

1.  Understand the fundamentals of big data

1. Analyse the purpose of big data
2. Analyse the sources of big data
3. Evaluate the benefits of using big data sets
4. Analyse the different uses of big data sets
5. Analyse the problems associated with using big data
6. Analyse the ethical concerns associated with using big data for decision making
7. Define the terms:

           • Volume

           • Variety

           • Velocity

           • Volumeeracity of data

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2.  Understand the structure, size and security of big data

1. Differentiate structured and unstructured data
2. Evaluate data storage methods and their characteristics
3. Analyse the problems associated with using and storing big data
4. Investigate the concepts of distributed computing with big data
5. Analyse the risks associated with big data

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3.  Understand the characteristics of data analysis

1. Analyse the importance of analysing data
2. Evaluate how to establish data trends in big data sets
3. Produce analytical and statistical representations of data

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4.  Be able to present information from large data sets

1. Analyse methods used for presenting large data sets
2. Explain target audience requirements
3. Prepare and present a summary presentation of information from large data sets
4. Identify areas for improvement based on data analysis

• The assessment strategy for this course is designed to test all the learning outcomes.
• Learners must demonstrate successful achievement of all learning outcomes to pass the course.

• The assessment criteria for a pass will be presented with the summative exercise.
• Further information and guidance on the assessment will be made available through the tutor.

To pass the unit a 40% overall grade must be achieved.