Presentaciones a Congresos
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Browsing Presentaciones a Congresos by Subject "ALMACENES DE DATOS"
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ponencia en congreso.listelement.badge From conceptual to logical ETL design using BPMN and relational algebra(2019) Awiti, Judith; Vaisman, Alejandro Ariel; Zimányi, Esteban"Extraction, transformation, and loading (ETL) processes are used to extract data from internal and external sources of an organization, transform these data, and load them into a data warehouse. The Business Process Modeling Notation (BPMN) has been proposed for expressing ETL processes at a conceptual level. This paper extends relational algebra (RA) with update operations for specifying ETL processes at a logical level. In this approach, data tasks can be automatically translated into SQL queries to be executed over a DBMS. An extension of RA is presented, as well as a translation mechanism from BPMN to the RA specification. Throughout the paper, the TPC-DI benchmark is used for comparing both approaches. Experiments show the efficiency of the resulting ETL flow with respect to the Pentaho Data Integration tool."ponencia en congreso.listelement.badge Modelling and querying star and snowflake warehouses using graph databases(2019) Vaisman, Alejandro Ariel; Besteiro, María Florencia; Valverde Melito, Maximiliano Javier"In current “Big Data” scenarios, graph databases are increasingly being used. Online Analytical Processing (OLAP) operations can expand the possibilities of graph analysis beyond the traditional graphbased computation. This paper studies graph databases as an alternative to implement star and snowflake schemas, the typical choices for data warehouse design. For this, the MusicBrainz database is used. A data warehouse for this database is designed, and implemented over a Postgres relational database. This warehouse is also represented as a graph, and implemented over the Neo4j graph database. A collection of typical OLAP queries is used to compare both implementations. The results reported here show that in ten out of thirteen queries tested, the graph implementation outperforms the relational one, in ratios that go from 1.3 to 26 times faster, and performs similarly to the relational implementation in the three remaining cases."