| Study programme competencies |
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Code
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Study programme competences
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| A46 |
Capacidade de integrar solucións de tecnoloxías da información e as comunicacións e procesos empresariais para satisfacer as necesidades de información das organizacións, permitíndolles alcanzar os seus obxectivos de forma efectiva e eficiente, e dándolles así vantaxes competitivas. |
| B3 |
Capacidade de análise e síntese |
| B5 |
Habilidades de xestión da información |
| C3 |
Utilizar as ferramentas básicas das tecnoloxías da información e as comunicacións (TIC) necesarias para o exercicio da súa profesión e para a aprendizaxe ao longo da súa vida. |
| C7 |
Asumir como profesional e cidadán a importancia da aprendizaxe ao longo da vida. |
| C8 |
Valorar a importancia que ten a investigación, a innovación e o desenvolvemento tecnolóxico no avance socioeconómico e cultural da sociedade. |
| Learning aims |
| Learning outcomes |
Study programme competences |
| Coñecer os conceptos de bases de datos necesarios para afrontar o proceso ETL, entender o proceso analítico e diferencialo do operacional, coñecer a arquitectura dun almacén de datos e saber efectuar o deseño e a explotación do mesmo, coa orientación á toma de decisións e incluíndo a utilización de ferramentas de minería de datos. |
A46
|
B3
B5
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C3
C7
C8
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| Contents |
| Topic |
Sub-topic |
| Conceptos de Bases de Datos |
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Introduction to Data Warehouse
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| Design of Data Warehouse |
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| Data Mining |
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| Planning |
| Methodologies / tests |
Competencies |
Ordinary class hours |
Student’s personal work hours |
Total hours |
| Laboratory practice |
A46 B3 B5 C3 C7 C8 |
14 |
21 |
35 |
| Problem solving |
A46 B3 B5 C3 C7 C8 |
7 |
14 |
21 |
| Workbook |
A46 B3 B5 C7 C8 |
0 |
14 |
14 |
| Mixed objective/subjective test |
A46 B3 B5 C3 C7 C8 |
3 |
0 |
3 |
| Supervised projects |
A46 B3 B5 C3 C7 C8 |
0 |
14 |
14 |
| Guest lecture / keynote speech |
A46 B3 B5 C7 C8 |
21 |
42 |
63 |
| |
| Personalized attention |
|
0 |
|
0 |
| |
| (*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. |
| Methodologies |
|
Methodologies |
Description |
| Laboratory practice |
Son clases nas que se desenvolven as competencias procedimentais relacionadas cos contidos da asignatura.
Nelas realizaranse probas e exercicios cuxo obxetivo é madurar os conceptos das clases teóricas, e introduciranse novos conceptos de carácter práctico que acompañaranse de exercicios. |
| Problem solving |
Clases nas que se discutirán as estrategias de solución de diversos problemas propostos. |
| Workbook |
Se propondrá a lectura de diversos traballos que complementen e axuden a entender os conceptos plantexados. |
| Mixed objective/subjective test |
Examen da asignatura que combina conceptos teóricos, prácticos e problemas. |
| Supervised projects |
Trabajos realizados baixo a orientación do profesorado, cuxo obxetivos é que os estudintes asuman a responsabilidade do seu propio aprendizaxe e que aprenden "cómo hacer". |
| Guest lecture / keynote speech |
Clases teóricas nas que se expoñen os contidos fundamentais da materia, que poden acompañarse da propuesta e a resolución de exemplos. |
| Personalized attention |
|
Methodologies
|
| Laboratory practice |
| Problem solving |
|
| Description |
| Both for the ICT practicals and for problem solving, the teaching staff will provide solutions and/or answer the doubts and questions that may arise. A more personalized attention will be developed in the tutorials. |
|
| Assessment |
|
Methodologies
|
Competencies |
Description
|
Qualification
|
| Laboratory practice |
A46 B3 B5 C3 C7 C8 |
The maximum mark will be 4 points out of 10 of the subject. The practice must be done individually or in small groups and will be defended orally. |
40 |
| Mixed objective/subjective test |
A46 B3 B5 C3 C7 C8 |
The maximum mark will be 3 points out of 10 for the subject. Several tests will be held during the course, dealing with theoretical concepts and practical assimilation of the subject. |
30 |
| Supervised projects |
A46 B3 B5 C3 C7 C8 |
The maximum mark of the works will be 3 points. |
30 |
| |
|
Assessment comments |
NOT SHOW: At the first opportunity, the student who does not do the laboratory practice will have the grade of NOT SHOW. At the second opportunity any of the parts of the evaluation can be recovered, so that the grades of this opportunity always substitute those of the first one. The student who does not make up any part of the evaluation will have a grade of NO SHOW. ACADEMIC DISPENSATION: Students officially enrolled part-time who have been granted an official dispensation from attending classes, as stipulated in the regulations of this University, must contact with the responsible of the course within the first two weeks to establish the conditions for submitting and defending the practical exercises and the supervised project. ADVANCED OPPORTUNITY: The evaluation in the advanced opportunity will consist of: mixed test (30% of the qualification), practice (40% of the qualification) and supervised project (30% of the qualification). |
| Sources of information |
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Basic
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Inmon, W. H. (2002). Building the Data Warehouse, 3nd edition. Wiley
Sharda, R. Delen, D.; Turban, E. (2014). Business Intelligence: A managerial perspective on analytics. Prentice Hall
Williams, G. (2011). Data Mining with Rattle and R. Springer
Tan, P.; Steinbach, M.; Kumar, V. (2006). Introduction to Data Mining . Addison-Wesley
Kimball, R.; Ross, M.; Thornthwaite, W.; Mundy, J.; Becker, B. (2008). The Data Warehouse Lifecycle Toolkit, 2nd edition. John Wiley and Sons
Kimball, R.; Ross, M (2013). The Data Warehouse Toolkit, 3rd edition. Wiley
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Complementary
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Golfarelli, M.; Rizzi, S. (2009). Data Warehouse Design: Modern Principles and Methodologies . McGraw-Hill
García-Molina, H.; Ullman, J.; Widom, J. (2009). Database System. The complete book.. Prentice Hall
Mazón López, N.; Pardillo Vela, J.; Trujillo Mondejar. J. C. (2011). Diseño y explotación de almacenes de datos . Editorial Club Universitario
Elmasri, R.; Navathe, S. (2011). Fundamentals of Database Systems. Addison-Wesley
Inmon, W. H.; Strauss, D.; Neushloss, G. (2008). The Architecture for the Next Generation of Data Warehousing . Morgan Kaufman
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| Recommendations |
| Subjects that it is recommended to have taken before |
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| Subjects that are recommended to be taken simultaneously |
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| Subjects that continue the syllabus |
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