What is he best known for?
The fields of study he is best known for:
- Database
- Operating system
- Programming language
The scientist’s investigation covers issues in Data warehouse, Information retrieval, Database, Workflow and Software.
Alkis Simitsis interconnects Set, Scalability, Software engineering and Semantic Web in the investigation of issues within Data warehouse.
The various areas that Alkis Simitsis examines in his Information retrieval study include Web service and Service.
His research in Workflow intersects with topics in Data model, Data integration and Data mining.
The study incorporates disciplines such as Conceptual model, Semantics and Personalization in addition to Software.
His Personalization study incorporates themes from Extensibility and Metamodeling.
His most cited work include:
- Conceptual modeling for ETL processes (292 citations)
- Optimizing ETL processes in data warehouses (173 citations)
- Data integration flows for business intelligence (149 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Data warehouse, Database, Information retrieval, Workflow and Distributed computing.
His studies deal with areas such as Software, Software engineering, Business intelligence and Personalization as well as Data warehouse.
His research integrates issues of Ontology, Software deployment, Set and Source data in his study of Database.
His Information retrieval research is multidisciplinary, relying on both Online analytical processing and Dimensional modeling.
His Workflow research includes elements of Database-centric architecture, Graph, Correctness, Fault tolerance and Collaborative software.
His Distributed computing research integrates issues from Workload, Parallel computing, Real-time computing, Variety and Cloud computing.
He most often published in these fields:
- Data warehouse (45.16%)
- Database (29.84%)
- Information retrieval (21.77%)
What were the highlights of his more recent work (between 2015-2021)?
- Distributed computing (15.32%)
- Big data (5.65%)
- Workload (4.03%)
In recent papers he was focusing on the following fields of study:
Distributed computing, Big data, Workload, Graph and Workflow are his primary areas of study.
The concepts of his Distributed computing study are interwoven with issues in Cloud computing and Application performance management.
His Big data study combines topics from a wide range of disciplines, such as Stack, Systems architecture and PATH.
He combines subjects such as Multi-core processor, Parallel computing, Online analytical processing, Scheduling and Robustness with his study of Workload.
His work in the fields of Graph database overlaps with other areas such as Computing systems.
His study in the field of Workflow technology also crosses realms of Business process.
Between 2015 and 2021, his most popular works were:
- The many faces of data-centric workflow optimization: a survey (19 citations)
- Incremental Consolidation of Data-Intensive Multi-Flows (14 citations)
- Extraction, Transformation, and Loading (14 citations)
In his most recent research, the most cited papers focused on:
- Database
- Operating system
- Programming language
His main research concerns Workflow, Workflow technology, Big data, Data management and Business process.
His work carried out in the field of Workflow brings together such families of science as Data flow diagram, Data integration and Business intelligence.
His Workflow technology research incorporates elements of Database-centric architecture, Data type, Data science and Data analysis.
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