Chapter 9 - Database Systems
General Outcomes
- Recognize fundamental knowledge of the role, structure, and characteristics of database systems, e.g.,
- The rationale for collecting, processing, and analyzing data in various environments.
- Basic ideas of the relational models and alternatives to it.
- The kinds of files used to store data and important tradeoffs involved in designing and implementing the database for a particular purpose.
- Computers are used to analyze data for the purpose of discovering inferences that can be made from that data rather than to look of specific data (data mining).
- The capability of computer analysis to identify individuals without personally identifiable information, e.g., zip code and birthdate.
- Apply knowledge/understanding of database technology in examining security and societal issues, e.g.,
- Analyze actual or proposed uses of database technology legal, ethical/moral, information security, correctness, etc. issues taking into account the data and people involved.
- Analyze various issues to formulate responsibility and liability of various stakeholders, i.e., retail business, data brokers, purchasers of data, government, and users/consumers.
Learning Objectives
By the end of this unit students should be able to:
- Explain the difference between a schema and a subschema.
- Given a particular domain and one or more “roles” within that domain, identify data that would be part of the subschema for each “role”
- Explain the different layers in a modern database implementation (Figure 9.2)
- Identify potential redundancy in a dataset and suggest how different relation tables can reduce/eliminate that redundancy.
- Define the concept of a/an [ attribute | relation | tuple ]
- Identify and/or explain the purpose of the [JOIN | PROJECT | SELECT ] operation in database queries.
- Given a description of a database and one or more relational operations, explain the results of the operation(s).
- Explain and give an example of the data mining technique of [class description | class discrimination | cluster analysis | association analysis | outlier analysis | sequential pattern analysis].
- Given a set of data and a need, identify which data mining technique would solve the need.