Rob Gleasure R.Gleasure@ucc.ie robgleasure.com IS6146 Databases for Management Information Systems Lecture 12: Exam Revision Rob Gleasure R.Gleasure@ucc.ie robgleasure.com

The exam

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

Exam structure (continued) Question 1 and 2 Balance of understanding and doing things Discuss topics referencing real-world examples Typically broken down into multiple parts Question 3 Extrapolation question Provocative statement for you to discuss Just one part Most questions will combine multiple themes

Theme 1: Structured data, DBMS, and SQL Why are structured SQL-based relational databases useful? What needs do they address that other technologies do not? How are the different DBMS better or worse than one another – when would you use one over another (e.g. MS Access over Oracle)? What are views, indices, defined procedures, triggers, etc. and why are they useful? What practical examples can you draw upon to illustrate the value of these different features of relational databases?

Theme 2: Unstructured data and business analytics What is unstructured data, what are the sources of unstructured data, and why is it important? What are regression, t-tests, and analysis of variance and what types of problems do they solve? What are classification, clustering, text mining, and social graphing and what types of problems do they solve? What practical examples can you draw upon to illustrate the value of these techniques?

Theme 3: Semi-structured data What is semi-structured data, how is it different from structured and unstructured data, and why is it important for modern organisations? How can crowds on the web act to create and organise information dynamically on the web? What’s value can be obtained by analysing social media data? What’s a practical example of this?

Theme 4: Alternative data stores What’s the difference between OLTP and OLAP and why is each important? What types of NoSQL data stores exist and what are the advantages/disadvantages associated with each What are examples where you might use one over the other? Why might you use multiple complementary data-related technologies? Explain the mapreduce concept and how it is applied in Hadoop What practical examples can you draw upon to illustrate the value of analysing OLTP and OLAP data?

Questions? This is your chance to ask! Do you feel confident about the structure of the exam? Do you feel confident you know what to revise? Do you feel confident you know what I’m expecting in an answer?