IS6125 Database Analysis and Design Lecture 12: Semester Review and Exam Preparation Rob Gleasure R.Gleasure@ucc.ie www.robgleasure.com

IS6125 Today’s session Subjects covered and the types of questions to expect Essay style questions Modelling questions General stuff Questions?

Making new connections Types of learning Application Doing things Reflection Examples Understanding things Making new connections

Exam structure Three questions, answer two 90 minutes You must answer Question 1 You may choose to answer either Question 2 or Question 3 All questions carry equal marks Dictionaries may be used for international students, however you will need to coordinate with the International Office in advance Students registered with DSS may be allocated additional time or alternative resources, however you will need to coordinate with the DSS Office in advance

Question 1 – doing things ERDs Can be SSADM and/or Chen’s Modelling question will expect A model Constraints Assumptions You may also be asked to discuss issues, such as Differences between stages of ER modelling The reasons for a staggered approach to data modelling Commonly encountered issues

Question 1 – doing things (cont.) DFDs Can be context-level or level 1 Either model will expect A model Assumptions You may also be asked to discuss issues, such as The different values of context-level and level 1 diagrams The reasons for a staggered approach to data modelling Commonly encountered issues

Question 1 – doing things (cont.) Normalisation Question will expect you to normalise a table to the third form Don’t be afraid to identify assumptions, where you feel they require further discussion You may also be asked to discuss issues, such as The reasons for normalising a table, i.e. redundancy The three Armstrong axioms

Question 2 – understanding things Topics covered Big data What are the three Vs? When is data ‘big data’? How and why did we get from ‘small data’ to ‘big data’? What does big data let businesses do that they couldn’t do previously? What businesses are a good example off this? What are the issues and challenges arising from big data? Can you use contrasting examples of different businesses to discuss each of these headings?

Question 2 – understanding things (cont.) Topics covered Datafication and the Internet of Things What is data and how does something become ‘datafied’? How and why did cloud technologies evolve? What does it mean in terms of technological and business capabilities? What is the Internet of Things? What does the future hold? Can you use contrasting examples of different businesses to discuss each of these headings?

Question 2 – understanding things (cont.) Topics covered Business intelligence and the different types of data What types of data exist, e.g. self-reported, exhaust, profile How do we move from descriptive analytics to prescriptive analytics? How do we get from an individual case to a large-scale pattern, and back again? What are the challenges of translating intelligence from an individual case to large-scale patterns, and back again? What businesses exemplify the ability to generate intelligence from the increased capacity for data handling, and why? Can you use contrasting examples of different businesses to discuss each of these headings?

Question 2 – understanding things (cont.) Topics covered Privacy and the ethical cost of data Why is data sensitive? What are the threats to privacy? Why are digital businesses more reliant on trust than traditional businesses? What is the cost of data for a user? Why does data privacy matter?

Question 3 – making connections Presented with a statement or idea and asked for your opinion E.g. Peter Drucker famously said “What gets measured gets managed”. Critically discuss this statement in the context of big data, using examples from specific businesses or your own experiences to illustrate your answer Just one part (no breakdown into (a), (b), etc.) You have to decide how to apply what you have learned to form a meaningful answer

Writing style and grammar

Answering Questions Exam technique Manage your time Plan your answers Say it simply but use the keywords from the semester, e.g. if you are talking about ‘big data’, call it big data – you don’t need to get creative Sketch out your diagrams very quickly as roughwork if you’re not sure how to make them fit together Answer your best questions first Use examples Have these lined up as part of your revision

Sample* rubric Evaluation of answers Criteria Qualities Ratio of marks Understanding Accuracy 30   Completeness Links to other material 20 Further learning Application Idenitification of ambiguity Creative extrapolation feasibility (is it true?) 40 novelty (is it new?) 35 value (is it interesting?) Example questions   Question style Example format Understanding Application Creative extrapolation Essay Compare and contrast concepts X and Y (30 marks) 60 20 Discuss an example where concept X added value (10 marks) For that example, what would you have done differently (10 marks) Modelling/SAD Why draw a diagram of type X (10 marks) Draw diagram X for this narrative (30 marks) State your assumptions (10 marks) Unstructured Critique this statement using examples (50 marks)