Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/37907
Title: | Logical big data integration and near real-time data analytics |
Author: | Silva, Bruno Moreira, José de C. Costa, Rogério Luís |
Keywords: | Big data integration Distributed databases Near real-time OLAP |
Issue Date: | 12-May-2023 |
Publisher: | Elsevier |
Abstract: | In the context of decision-making, there is a growing demand for near real-time data that traditional solutions, like data warehousing based on long-running ETL processes, cannot fully meet. On the other hand, existing logical data integration solutions are challenging because users must focus on data location and distribution details rather than on data analytics and decision-making. EasyBDI is an open-source system that provides logical integration of data and high-level business-oriented abstractions. It uses schema matching, integration, and mapping techniques, to automatically identify partitioned data and propose a global schema. Users can then specify star schemas based on global entities and submit analytical queries to retrieve data from distributed data sources without knowing the organization and other technical details of the underlying systems. This work presents the algorithms and methods for global schema creation and query execution. Experimental results show that the overhead imposed by logical integration layers is relatively small compared to the execution times of distributed queries. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/37907 |
DOI: | 10.1016/j.datak.2023.102185 |
ISSN: | 0169-023X |
Appears in Collections: | DETI - Artigos IEETA - Artigos |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Logical-big-data-integration-and-near-real-time-d_2023_Data---Knowledge-Engi.pdf | 1.97 MB | Adobe PDF |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.