CCO - 630 - Non-Conventional Databases

Total of Credits: 8
Hours for Theoretical Classes: 60
Hours for Exercises or Seminars: 60

Objective

To present relevant concepts, techniques and tools in the non-conventional database area. Data models for non-conventional applications will be analyzed and the main characteristics of database management systems to support the development of such applications will be studied.

Catalog Description

  • Conventional versus unconventional data. Evolution of data management requirements and database models
  • Concepts, techniques and tools in the non-conventional database area
  • Main features of database management systems to support the development of non-conventional applications

Main Bibliography

  1. Elmasri, R. Navathe, S.B. “Fundamentals of Database Systems”, 7a. Ed., Addison-Wesley, 2016.
  2. Dittrich, K., Kotz, A., and Mulle, J. [1986] “An Event/Trigger Mechanism to Enforce Complex Consistency Constraints in Design Databases,” in ACM SIGMOD Record, 15:3, 1986.
  3. Allen, J. [1983] “Maintaining Knowledge about Temporal Intervals,” in CACM 26:11, November 1983, pp. 832–843.
  4. Carvalho, V. “PostgreSQL: Banco de dados para aplicações web modernas”, Ed. Casa do Código, 2017
  5. Berson, A., Smith, S. Data Warehousing, Data Mining, and OLAP. McGraw-Hill, 1997. ISBN 0-07-006272-2. INMON, W.H. Building the Data Warehouse, 4th edition. Wiley Publishing Inc, 2005. ISBN 0-7645-9944-5.
  6. MALINOWSKI, E.; ZIMÁNYI, E. Advanced Data Warehouse Design: From Conventional to Spatial and Temporal Applications. Springer, 1st edition, 2008. ISBN 978-3-540-74404-7 (Impresso), 978-3-540-74405-4 (Online).

Complementary Bibliography

  1. O’NEIL, E.; O’NEIL, P.; WU, K. Bitmap Index Design Choices and Their Performance Implications. In: 11TH INTERNATIONAL DATABASE ENGINEERING AND APPLICATIONS SYMPOSIUM. Proceedings… Banff, Canada: IEEE Computer Society, 2007. p. 72-84. 
  2. O'NEIL, P.; GRAEFE, G. Multi-table joins through bitmapped join indices. ACM SIGMOD Record, v.24, n.3, p.8-11, 1995.
  3. PAPADIAS, D.; KALNIS, P.; ZHANG, J.; TAO, Y. Efficient OLAP Operations in Spatial Data Warehouses. Proceedings of the 7th International Symposium On Spatial And Temporal Databases. Redondo Beach, CA, USA: Springer-Verlag, 2001. p.443-459.
  4. WREMBEL, R., KONCILIA, C. Data Warehouses and OLAP: Concepts, Architectures and Solutions, 1st edition. IRM Press, 2007. ISBN 1-59904365-3. Artigos de periódicos e eventos científicos referentes ao processamento analítico de dados.