Databases II I-NI7O>BD-II
A. Lecture (20h) - detailed learning content:
1. Developing database applications. Concepts of database modelling. Data models: definition, classifications, characteristics.
2. Introduction to issues related to database application development: database application design, information system, information system design cycle, database system development process.
3. Relational database schema design methodology. Data modelling (E-RD). Conceptual modelling - purpose and stages. Entity-Relationship Model (E-R). Relationships and types of relationships in the E-R model. Relationships with time-dependent entity participation. Specialisation-generalisation. Transformation of EER to RDB.
4. Object-oriented modelling (UML). CASE tools. Functional relationships - definitions, rules. Relationship ties. Multivalued relationships. Normalization of logical relation diagrams. Postulate of normalisation. Functional relations. Multivalued relations. Connectional relations. Normal forms of relations.
5. Overview of database management systems (DBMS). Structure and physical structures of a DBMS. SZBD functions. Roles in the database environment. Layered structure of the SZBD. ANSI-SPARC structure schema mapping. Architecture of a multi-access SZBD. Alternative client-server topologies.
6. Classes of database systems. Microsoft SQL Server architecture: product variations, service architecture, tier architecture, major database engine components. Microsoft SQL Server system instances: databases, schemas, objects. The physical layout of the database. File and file group design principles.
7. Interfaces - implementation of access to data sources. Overview of database access technologies.
8. Security of databases. Security requirements. SQL security model. Data sensitivity. Security versus precision. The problem of inference and aggregation. Multi-level databases. Database security versus standards.
9. Generating a database server, databases and their schemas. Concurrency and transactions. Cursors, visual programming. Database security, backups. Database management, protection strategies, user definition. Query optimisation, indexes. Database optimization.
10. Data replication. Object-oriented data model, object-oriented databases. Relational-object databases. Partial-structural model databases. Distributed databases. Data warehouses. Databases on the Internet.
B. Laboratory (20h) - detailed learning content:
1. Introduction to the laboratory - organisation of the classes in the semester, e-learning materials, requirements and conditions for obtaining credit, drawing of topics for individual database projects, discussion of the stages of project implementation. Analysis and programming of preset DML triggers to selected test database tables. Database - case study: analysing the problem and defining the requirements of a database-based application. Construction of a conceptual model (DZE).
2. Transformation to logical model, normalisation to 3NF.
3. Database generation, schema definition using supporting tools. Development of scripts to define/modify the database schema.
4. Entering data using SQL commands, from a file, from other tables.
5. Written test 1. Creating database diagrams in MS SQL Management Studio environment.
6. Definition of users and their privileges, delegation of privileges, inheritance of privileges, role of database administrator.
7. Transactions, working at different levels of isolation.
8. Utilities - backup, transaction log translation, database unloading and loading.
9. Query optimisation, indexes. Data replication. Communication with the database via ODBC interface.
10. Written test 2. Presentation and evaluation of projects.
The realisation of the presented subject matter and achieving the intended learning outcomes will be realised within 40 contact hours (lectures + laboratory exercises) and approximately 30 hours of individual project topics (within the student's own work time).
|
Term 2021/2022-Z:
None |
Term 2022/2023-L:
None |
Term 2023/2024-L:
None |
Term 2024/2025-L:
None |
Course coordinators
<b>Final assessment</b>
Term 2024/2025-L: | Term 2022/2023-L: (in Polish) zaliczenie przedmiotu jest efektem zaliczenia wykładu z semestru 3., ćwiczeń laboratoryjnych z semestrów 3. i 4. oraz egzaminu w semestrze 4. Ocena końcowa jest wypadkową tych czterech elementów.
| Term 2023/2024-L: |
<b>Prerequisites</b>
Term 2024/2025-L: | Term 2022/2023-L: (in Polish) Wymagane jest zaliczenie modułu Bzay danych I (IZI.36 – sem. 3). Wymagań dodatkowych brak.
| Term 2023/2024-L: |
<b>Basic literature</b>
Term 2024/2025-L: | Term 2022/2023-L: (in Polish)
| Term 2023/2024-L: |
<b>Supplementary literature</b>
Term 2024/2025-L: | Term 2022/2023-L: (in Polish) Karwin B.: Antywzorce języka SQL. Jak unikać pułapek podczas programowania baz danych, Helion, Gliwice, 2012
| Term 2023/2024-L: |
<b>Other information</b>
Term 2024/2025-L: | Term 2022/2023-L: (in Polish) brak
| Term 2023/2024-L: |
Learning outcomes
Knowledge
Related directional learning outcomes:
IF1A_W08
Verification metods:
Knowledge
Related directional learning outcomes:
IF1A_W08
Verification metods:
Knowledge
Related directional learning outcomes:
IF1A_W08
Verification metods:
Skills
Related directional learning outcomes:
IF1A_U19
Verification metods:
Skills
Related directional learning outcomes:
IF1A_U28
Verification metods:
Skills
Related directional learning outcomes:
IF1A_U29
Verification metods:
Social competence
Related directional learning outcomes:
IF1A_K04
Verification metods:
Assessment criteria
A. Students will receive credit for the lecture on the basis of a passing grade in the written examination - the passing grade for the OE lecture is determined by the examination grade. In the case of classes conducted remotely, the exam will be conducted online on the platform elearning.ubb.edu.pl. A prerequisite for the written examination is a pass mark from the laboratory exercises. Students may write the resit exam in the resit session or at later dates with the approval of the dean.
B. A student obtains a pass mark for the laboratory on the basis of positive grades from two written tests in a semester and a grade from the database project - the pass mark for the OL laboratory is determined by the arithmetic mean of the test grades and the project grade. In the case of classes conducted remotely, tests are realised in the form of assignments made available online temporarily and sent back to the elearning.ubb.edu.pl platform within a specified deadline.
C. The final grade OK is a weighted average of the grades: from the OE exam and the OL laboratory credit, according to the formula: OK = 0.6* OE + 0.4*OL.
Bibliography
A. List of primary literature:
1. Allen S.: Modelowanie danych, Helion, Gliwice 2006
2. Connolly T., Begg C.: Systemy baz danych, Wydawnictwo RM, Warszawa 2004
3. Elmsari R., Navathe S.B.: Wprowadzenie do systemów baz danych, wyd. VII, Helion, Gliwice 2019
4. Garcia-Molina H., Ullman J., Widom J.: Systemy baz danych. Kompletny podręcznik. wyd. II, Helion, Gliwice, 2011
5. Ullman J., Widom J.: Podstawowy kurs systemów baz danych, wyd. III, Helion, Gliwice, 2011
B. List of supplementary literature:
1. Karwin B.: Antywzorce języka SQL. Jak unikać pułapek podczas programowania baz danych, Helion, Gliwice, 2012.
2. Elmsari R., Navathe S.B.: Wprowadzenie do systemów baz danych, wyd. VII, Helion, Gliwice 2019
3. Pelikant A.: Hurtownie danych. Od przetwarzania analitycznego po raportowanie, wyd. II, Helion, Gliwice 2021
4. Harrison G.: NoSQL, NewSQL i BigData. Bazy danych następnej generacji, Helion, Gliwice 2019