1. IS6125 Database Analysis and Design Lecture 12: Semester Review and Exam Preparation
Rob Gleasure

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

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

4. 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

5. 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

6. 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

7. 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

8. 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?

9. 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?

10. 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?

11. 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?

12. 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

13. Writing style and grammar

14. 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

15. 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)