IMDM 2013 - 2013 Workshop on In-memory Data Management and Analytics
Topics/Call fo Papers
The discussion of new opportunities through innovative decision processes using in-memory data management is the aim of the workshop In-Memory Data Management. It focuses on new applications, technological issues and aspects of practical implementation:
* What are promising potential usage areas of in-memory data management for companies in various industries?
* What new opportunities arise for business application systems and platforms?
Topics of interest include, but are not limited to, practical areas that span a variety of aspects of in-memory data management:
* Potential Applications: innovative enterprise applications build on in-memory technology; potential areas of use and benefit assessments
* BI Architectures: novel reference architectures of business intelligence platforms with in-memory technologies, e.g. virtual data warehouses
* Analytical Applications: in-memory DBMS supporting current trends in analytics, e.g. self-service BI, predictive analytics, Big Data analytics, alternative data structures and workloads (graph, matrices, etc.)
* Hybrid Applications: consolidation of transactional (OLTP) and analytical (OLAP) enterprise applications
* Practical Implementation: deployment, provisioning and sizing of in-memory applications
* What are promising potential usage areas of in-memory data management for companies in various industries?
* What new opportunities arise for business application systems and platforms?
Topics of interest include, but are not limited to, practical areas that span a variety of aspects of in-memory data management:
* Potential Applications: innovative enterprise applications build on in-memory technology; potential areas of use and benefit assessments
* BI Architectures: novel reference architectures of business intelligence platforms with in-memory technologies, e.g. virtual data warehouses
* Analytical Applications: in-memory DBMS supporting current trends in analytics, e.g. self-service BI, predictive analytics, Big Data analytics, alternative data structures and workloads (graph, matrices, etc.)
* Hybrid Applications: consolidation of transactional (OLTP) and analytical (OLAP) enterprise applications
* Practical Implementation: deployment, provisioning and sizing of in-memory applications
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Last modified: 2013-03-31 13:46:59