Checking date: 29/05/2024


Course: 2024/2025

Files and Databases
(18278)
Bachelor in Applied Mathematics and Computing (Plan: 433 - Estudio: 362)


Coordinating teacher: CALLE GOMEZ, FRANCISCO JAVIER

Department assigned to the subject: Computer Science and Engineering Department

Type: Compulsory
ECTS Credits: 6.0 ECTS

Course:
Semester:




Requirements (Subjects that are assumed to be known)
- Programming (1st year, 1st term) - Discrete Mathematics (1st year, 2nd term) - Algorithms and Data Structures (2st year, 2nd term) - Computer Structure (2nd year, 1st term)
Skills and learning outcomes
CB1. Students have demonstrated possession and understanding of knowledge in an area of study that builds on the foundation of general secondary education, and is usually at a level that, while relying on advanced textbooks, also includes some aspects that involve knowledge from the cutting edge of their field of study. CB2. Students are able to apply their knowledge to their work or vocation in a professional manner and possess the competences usually demonstrated through the development and defence of arguments and problem solving within their field of study. CB3. Students have the ability to gather and interpret relevant data (usually within their field of study) in order to make judgements which include reflection on relevant social, scientific or ethical issues. CB4. Students should be able to communicate information, ideas, problems and solutions to both specialist and non-specialist audiences. CB5. Students will have developed the learning skills necessary to undertake further study with a high degree of autonomy. CG1. Students are able to demonstrate knowledge and understanding of concepts in mathematics, statistics and computation and to apply them to solve problems in science and engineering with an ability for analysis and synthesis. CG3. Students can solve computationally with the help of the most advanced computing tools mathematical models coming from applications in science, engineering, economy and other social sciences. CG4. Students are able to show that they can analyze and interpret, with help of computer science, the solutions obtained from problems associated to real world mathematical models, discriminating the most relevant behaviours for each application. CG6. Students can search and use bibliographic resources, in physical or digital support, as they are needed to state and solve mathematically and computationally applied problems arising in new or unknown environments or with insufficient information. CE12. Students have shown that they know the main data structures, being able to use, design, and implement them determining its computational and storage complexity. CE18. Students know how to evaluate and select in an adequate way storage systems and database management systems and to adequately design storage and access structures, as well as applications that make use of them, including data visualization tools. RA2. Through sustained and well prepared argument and procedures, students will be able to apply their knowledge, their understanding and the capabilities to resolve problems in complex specialized professional and work areas requiring the use of creative and innovative ideas. RA3. Students must have the capacity to gather and interpret data and information on which they base their conclusions, including where relevant and necessary, reflections on matters of a social, scientific, and ethical nature in their field of study. RA5. Students must know how to communication with all types of audiences (specialized or not) their knowledge, methodology, ideas, problems and solutions in the area of their field of study in a clear and precise way. RA6. Students must be capable of identifying their own education and training needs in their field of study and the work or professional environment and organize their own learning with a high degree of autonomy in all types of contexts (structured or not).
Description of contents: programme
The descriptors associated with the subject are: File structures serial, sequential, hashed and indexed. Multidimensional access. Relational Data Model. Database Management Systems for Relational Databases. SQL database language: definition and manipulation. The program features the following agenda: ITEM 1. Introduction to Data Bases Storage and Files: Physical vs. Logical focuses Definition of Database ITEM 2. The Relational Statics Elements of the Relational Model. Description and notation. Inherent vs. Semantic Constraints ITEM 3. The Relational Dynamics Relational Algebra Data Manipulation through SQL ITEM 4. Advanced Relational Views Triggers ITEM 5. Introduction and Basic Concepts File Design. Goals of Physical Design. File Processing: Selection vs. Location ITEM 6. Base Structures Basic structures: Serial and Sequential Direct Access and Hashing Clusters ITEM 7. Auxiliary Structures Indexed Organization B Tree-structured indexes Special Indexes: bitmap Index supported Processes ITEM 8. Data Base Management Systems Architecture and Fundamentals of the RDBMS Oracle Internal Schema in the RDBMS Oracle Processes and Execution Plans the RDBMS Oracle ITEM 9. DB Paradigms & Analytic DB Storage characterization: OLTP vs. OLAP Introducing OLAP technologies: types, uses and tools.
Learning activities and methodology
THEORETICAL-PRACTICAL CLASSES. [44 hours with 100% classroom instruction, 1.67 ECTS] Knowledge and concepts students must acquire. Student receive course notes and will have basic reference texts to facilitate following the classes and carrying out follow up work. Students partake in exercises to resolve practical problems and participate in workshops and evaluation tests, all geared towards acquiring the necessary capabilities. TUTORING SESSIONS. [4 hours of tutoring with 100% on-site attendance, 0.15 ECTS] Individualized attendance (individual tutoring) or in-group (group tutoring) for students with a teacher. STUDENT INDIVIDUAL WORK OR GROUP WORK [98 hours with 0 % on-site, 3.72 ECTS] WORKSHOPS AND LABORATORY SESSIONS [8 hours with 100% on site, 0.3 ECTS] FINAL EXAM. [4 hours with 100% on site, 0.15 ECTS] Global assessment of knowledge, skills and capacities acquired throughout the course. METHODOLOGIES THEORY CLASS. Classroom presentations by the teacher with IT and audiovisual support in which the subject's main concepts are developed, while providing material and bibliography to complement student learning. PRACTICAL CLASS. Resolution of practical cases and problem, posed by the teacher, and carried out individually or in a group. TUTORING SESSIONS. Individualized attendance (individual tutoring sessions) or in-group (group tutoring sessions) for students with a teacher as tutor. LABORATORY PRACTICAL SESSIONS. Applied/experimental learning/teaching in workshops and laboratories under the tutor's supervision.
Assessment System
  • % end-of-term-examination 50
  • % of continuous assessment (assigments, laboratory, practicals...) 50

Calendar of Continuous assessment


Extraordinary call: regulations
Basic Bibliography
  • Cuadra, D., Castro, E., Iglesias, A., Martínez, P., Calle, J., de Pablo, C., Al'Jumaily, H., Moreno, L.. Desarrollo de Bases de Datos: casos prácticos desde el análisis a la implementación. Ra-Ma. 2ª ed. revisada y ampliada (2013)
  • Elmasri, R. y Navathe, S.. Fundamentals of Database Systems (7th ed.). Pearson Education. 2017
  • Oracle® . SQL*Plus. User's Guide and Reference. http://docs.oracle.com/database/121/SQPUG/E18404-12.pdf. 2013
  • Oracle® Database. SQL Language Reference. http://docs.oracle.com/database/121/SQLRF/E41329-17.pdf. 2015
Recursos electrónicosElectronic Resources *
Additional Bibliography
  • Date, C.J.. An introduction to database systems (7th edition).. Pearson Educación. 2001
  • Frakes, W. y Baeza-Yates, R., Eds.. Information retrieval. Data structures and algorithms.. Prentice Hall.. 1992
  • Gaede, O. and Günther,V. (1998).. Multidimensional Access Methods.. ACM Computing Surveys, Vol. 30, No. 2. . (c) 1998 ACM NY.
  • Guttman, A. . R-trees: A dynamic index structure for spatial searching. Procs. of the ACM SIGMOD 84, Int. Conference on Management of Data.. 1984
  • Livadas, Panos E.. File Structures: Theory and Practice.. Ed. Prentice-Hall Int. 1990
  • Ramakrishnan, R.; Gehrke, J.. Database management systems. WCB/McGraw Hill. . 3rd ed., 2012
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The course syllabus may change due academic events or other reasons.