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Students are introduced to the database engine architecture and typical user roles. They are briefly introduced to various database models. They learn to design small databases (including integrity constraints) using a conceptual model and implement them in a relational database engine. They get a hands-on experience with the SQL language, as well as with its theoretical foundation - the relational database model. They learn the principles of normalizing a relational database schema. They understand the fundamental concepts of transaction processing, controlling parallel user access to a single data source, as well as recovering a database engine from a failure. They are briefly introduced to special ways of storing data in relational databases with respect to speed of access to large quantities of data. This introductory-level course does not cover: Administration of database systems, debugging and optimizing database applications, distributed database systems, data stores.
Last update: Jirát Jiří (09.01.2014)
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Students will be able to: design and implement small databases and work with them effectively using the SQL language in a wide range of situations. understand theoretical foundations for subsequent courses, such as Database systems administration or specialized database-oriented courses (SQL, Database systems 2) in the second cycle degree programme. Last update: Jirát Jiří (31.01.2014)
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R:Date, C. J. Introduction to Database Systems, An (8th Edition). Addison Wesley, 2003. ISBN 0321197844. Last update: Jirát Jiří (09.01.2014)
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1. Bulk data processing concepts. DBMS architecture. Functions of individual components. 2. Data abstraction. Conceptual, database and physical level data model. 3. Conceptual data model. Basic constructs, integrity constraints. 4. Overview of database models - network, hierarchical, relational and object-relational model. 5. Relational data model. Relation, attributes, domains, relational database schema, DDL SQL. 6. Expressing integrity constraints through functional dependencies. Normal forms of relations. 7. Database query languages. Relational algebra, SQL. 8. [2] SQL: DDL, DCL, DML. 9. Relational schema design. Normalization using decomposition. Decomposition quality criteria. 10. Relational database schema design using a direct transformation from a conceptual schema. 11. Transactions, error recovery, concurrency control, data security and integrity. 12. Physical data model, tables as heaps, Rowid direct access, B* tree type index, bitmap index, indexed cluster, hashed cluster. Last update: Jirát Jiří (09.01.2014)
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https://edux.fit.cvut.cz/courses/BI-DBS (login necessary) Last update: Jirát Jiří (09.01.2014)
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Common user-level knowledge of Unix/Linux and MS Windows operating systems, ability to describe a solution to a problem algorithmically, and elementary knowledge of algebra and logic are expected. Active knowledge of a specific programming language is not required. Last update: Jirát Jiří (09.01.2014)
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| Teaching methods | ||||
| Activity | Credits | Hours | ||
| Účast na přednáškách | 1 | 28 | ||
| Příprava na přednášky, semináře, laboratoře, exkurzi nebo praxi | 0.5 | 14 | ||
| Práce na individuálním projektu | 1.5 | 42 | ||
| Příprava na zkoušku a její absolvování | 1.1 | 30 | ||
| Účast na seminářích | 1.5 | 42 | ||
| 6 / 6 | 156 / 168 | |||