CCO - 632 - Non-Conventional Data Warehouses and Cloud Databases

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

Objective

To present concepts, architectures, environments, methodologies, techniques, tools and software in the database area, emphasizing non- conventional data warehouses and cloud databases (databases for cloud computing environments). Regarding non-conventional data warehouses, spatial (geographic) data warehouses, spatial data warehouses with vague spatial objects, spatio-temporal data warehouses, image data warehouses and multimedia data warehouses will be discussed. With regard to cloud databases, the subjects of cloud data management, consistency, partitioning, fault tolerance, scalability and elasticity in the storage and recovery of data in the cloud will be investigated.

Catalog Description

  • Concepts, architectures, environments, methodologies, techniques, tools and software relevant to the subject “non-conventional data warehouses”
  • Spatial (geographic) data warehouses and spatial data warehouses with vague spatial objects.
  • Spatio-temporal data warehouses
  • Image data warehouses and multimedia data warehouses
  • Concepts, architectures, environments, methodologies, techniques, tools and software relevant to the subject “cloud databases”
  • Cloud data management. Database-as-a-Service (DaaS). NoSQL databases
  • CAP and BASE properties. Concepts of consistency, partitioning, distribution and fault tolerance
  • Scalability and elasticity in cloud data storage and retrieval

Main Bibliography

  1. VAISMAN, A., ZIMÁNYI, E. Data Warehouse Systems: Design and Implementation. 2014. 622 p.
  2. KLEPPMANN, M. Designing DataIntensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems. 2017. 562 p.
  3. MALINOWSKI, E and ZIMANYI, E. Advanced Data Warehouse Design: from conventional to spatial and temporal applications. 2008.
  4. SIQUEIRA, T., MATEUS, R., CIFERRI, R., TIMES, V., CIFERRI, C. Querying Vague Spatial Information in Geographic Data Warehouses. In: The 14th AGILE International Conference on Geographic Information Science, 2011, Utrecht, Holanda. Lecture Notes in Geoinformation and Cartography: Advancing Geoinformation Science for a Changing World, 2011. v. 1. p. 379-397.

Complementary Bibliography

  1. ABELLO A., SAMOS J., SALTOR F. YAM2: (yet another multidimensional model): An extension of UML. In Proceedings of the International Database Engineering and Applications Symposium (IDEAS02), 2002.
  2. ABELLO A., SAMOS J., SALTOR F. YAM2: a multidimensional conceptual model extending UML. Inf. Syst., 31(6):541-567, 2006. Encyclopedia of Data Warehousing and Mining. Idea Group Publishing, 2005.
  3. ROMERO O., ABELLO A. On the need of a reference algebra for olap. In Il Yeal Song, Johann Eder, and Tho Manh Nguyen, editors, DaWaK, volume 4654 of Lecture Notes in Computer Science, pages 99-110. Springer, 2007. DILO, A., BY, R.A., STEIN, A. A system of types and operators for handling vague spatial objects. IJGIS 21(4), 397-426, 2007.
  4. MATEUS, R. C. ; TIMES, V. C. ; SIQUEIRA, T. L. L. ; CIFERRI, R. R. ; Ciferri, Cristina Dutra de Aguiar. How Does the Spatial Data Redundancy Affect Query Performance in Geographic Data Warehouses? Journal of Information and Data Management, v. 1, p. 519-534, 2010.
  5. PARIMALA N., PAYAL PAHWA. Algebra for multiple cubes. International Journal of Information and Management Sciences, 21(3):285-313, 2010. 
  6. RIZZI S. Conceptual modeling solutions for the data warehouse, chapter 1, pages 1-26. 2007.
  7. SIQUEIRA, T., MATEUS, R., CIFERRI, R., TIMES, V., CIFERRI, C. Querying Vague Spatial Information in Geographic Data Warehouses. In: The 14th AGILE International Conference on Geographic Information Science, 2011, Utrecht, Holanda. Lecture Notes in Geoinformation and Cartography: Advancing Geoinformation Science for a Changing World, 2011. v. 1. p. 379-397.
  8. WREMBEL, R., KONCILIA, C. Data Warehouses and OLAP Concepts, Architectures and Solutions. IGI Global, 2006.