Information Management

Information Management (IM) (12%) For Computer Science Students


   IM1. Information models and systems [core]
   IM2. Database systems [core]
   IM3. Data modeling [core]
   IM4. Relational databases [elective]
   IM5. Database query languages [elective]
   IM6. Relational database design [elective]
   

Recommended Books:

1.    Database Systems by C.J. Date

2.    Modern Database Management by Fred R McFadden & Jeffry A. Hoffer

Information Management (IM) plays a critical role in almost all areas where computers are used. This area includes the capture, digitization, representation, organization, transformation, and presentation of information; algorithms for efficient and effective access and updating of stored information, data modeling and abstraction, and physical file storage techniques. It also encompasses information security, privacy, integrity, and protection in a shared environment. The student needs to be able to develop conceptual and physical data models, determine what IM methods and techniques are appropriate for a given problem, and be able to select and implement an appropriate IM solution that reflects all suitable constraints, including scalability and usability.

IM1. Information models and systems [1%] [core]
Minimum core coverage time: 3 hours
Topics:

• History and motivation for information systems
• Information storage and retrieval (IS&R)
• Information management applications
• Information capture and representation
• Analysis and indexing
• Search, retrieval, linking, navigation
• Information privacy, integrity, security, and preservation
• Scalability, efficiency, and effectiveness

Learning objectives:

1. Compare and contrast information with data and knowledge.
2. Summarize the evolution of information systems from early visions up through modern offerings, distinguishing their respective capabilities and future potential.
3. Critique/defend a small- to medium-size information application with regard to its satisfying real user information needs.
4. Describe several technical solutions to the problems related to information privacy, integrity, security, and preservation.
5. Explain measures of efficiency (throughput, response time) and effectiveness (recall, precision).
6. Describe approaches to ensure that information systems can scale from the individual to the global.

IM2. Database systems [2%] [core]

Minimum core coverage time: 3 hours
Topics:

• History and motivation for database systems
• Components of database systems
• DBMS functions
• Database architecture and data independence
• Use of a database query language

Learning objectives:

1. Explain the characteristics that distinguish the database approach from the traditional approach of programming with data files.
2. Cite the basic goals, functions, models, components, applications, and social impact of database systems.
3. Describe the components of a database system and give examples of their use.
4. Identify major DBMS functions and describe their role in a database system.
5. Explain the concept of data independence and its importance in a database system.
6. Use a query language to elicit information from a database.

IM3. Data modeling [2%] [core]

Minimum core coverage time: 4 hours
Topics:

• Data modeling
• Conceptual models (including entity-relationship and UML)
• Object-oriented model
• Relational data model

Learning objectives:

1. Categorize data models based on the types of concepts that they provide to describe the database structure -- that is, conceptual data model, physical data model, and representational data model.
2. Describe the modeling concepts and notation of the entity-relationship model and UML, including their use in data modeling.
3. Describe the main concepts of the OO model such as object identity, type constructors, encapsulation, inheritance, polymorphism, and versioning.
4. Define the fundamental terminology used in the relational data model .
5. Describe the basic principles of the relational data model.
6. Illustrate the modeling concepts and notation of the relational data model.

IM4. Relational databases [2%] [elective]

Topics:

• Mapping conceptual schema to a relational schema
• Entity and referential integrity
• Relational algebra and relational calculus

Learning objectives:

1. Prepare a relational schema from a conceptual model developed using the entity-relationship model
2. Explain and demonstrate the concepts of entity integrity constraint and referential integrity constraint (including definition of the concept of a foreign key).
3. Demonstrate use of the relational algebra operations from mathematical set theory (union, intersection, difference, and cartesian product) and the relational algebra operations developed specifically for relational databases (select, product, join, and division).
4. Demonstrate queries in the relational algebra.
5. Demonstrate queries in the tuple relational calculus.

IM5. Database query languages [3%] [elective]

Topics:

• Overview of database languages
• SQL (data definition, query formulation, update sublanguage, constraints, integrity)
• Query optimization
• QBE and 4th-generation environments
• Embedding non-procedural queries in a procedural language
• Introduction to Object Query Language

Learning objectives:

1. Create a relational database schema in SQL that incorporates key, entity integrity, and referential integrity constraints.
2. Demonstrate data definition in SQL and retrieving information from a database using the SQL SELECT statement.
3. Evaluate a set of query processing strategies and select the optimal strategy.
4. Create a non-procedural query by filling in templates of relations to construct an example of the desired query result.
5. Embed object-oriented queries into a stand-alone language such as C++ or Java (e.g., SELECT Col.Method() FROM Object).

  IM6. Relational database design [2%] [elective]

Topics:

• Database design
• Functional dependency
• Normal forms (1NF, 2NF, 3NF, BCNF)
• Multivalued dependency (4NF)
• Join dependency (PJNF, 5NF)
• Representation theory

Learning objectives:

1. Determine the functional dependency between two or more attributes that are a subset of a relation.
2. Describe what is meant by 1NF, 2NF, 3NF, and BCNF.
3. Identify whether a relation is in 1NF, 2NF, 3NF, or BCNF.
4. Normalize a 1NF relation into a set of 3NF (or BCNF) relations and denormalize a relational schema.
5. Explain the impact of normalization on the efficiency of database operations, especially query optimization.
6. Describe what a multivalued dependency is and what type of constraints it specifies.
7. Explain why 4NF is useful in schema design.