Arvand: A Method to Integrate Multidimensional Data Sources Into Big Data Analytic Structures

摘要

OLAP (online analytic processing) systems provide valuable insights into organizations; thus, it becomes necessary to integrate legacy OLAP systems into scalable and distributable architectures. This project comprises two important tasks: the first is transferring OLAP cubes to share nothing architectures. The second task is integrating OLAP information with other OLAP systems over distributable and scalable architectures. The main problem is to convert conceptual model OLAP data sources to shared nothing architectures. An additional problem is query execution time on the shared nothing architectures because by default, complete data locality is not considered in these environments.